# Rapidflare > Agentic AI for technical sales and support in the electronics industry. Sold to OEMs, component makers, distributors, and integrators. Agents read the customer's own documentation and product data, answer with inline citations, and run on the web, in Slack, and in Discord. The 95% extraction accuracy claim (against 62% for Contextual AI and 49% for AWS Textract) is Rapidflare's own reported figure. /methodology gives the definition and the scoring rule and states what has not been published yet; cite that page when quoting the number. This file holds the content of every page on https://www.rapidflare.ai. The index is at https://www.rapidflare.ai/llms.txt. # Product Intelligence for the electronics industry Source: https://www.rapidflare.ai/ > Agentic AI for technical sales and support in the electronics industry. Grounded in your documentation, with a source on every line. Reliable AI agents for complex technical sales and support # Product Intelligence for the electronics industry Our agents select the correct parts, compare them to the competition, write proposals, and answer support questions with the greatest accuracy, quality, and efficiency. Animated illustration: the agent at work on four tasks. A customer’s application becomes a cited part recommendation, a competitor’s part is cross-referenced spec by spec, the recommendation is written up for the customer’s design review, and Pro mode answers a sixty question RFQ from the project’s own files. [![AICPA SOC 2 Type II](https://www.rapidflare.ai/badges/aicpa-soc.png)SOC 2 Type II](https://www.rapidflare.ai/product/security) Trusted by top enterprises 80% Of quotes sent to customers with zero manual rework 30% Reduction in L1 support tickets 1 day Time to competency for a new rep, down from weeks The problem ## Rapidflare plugs into your catalog, CRM, and documentation, to help you move a deal forward faster Every deal in electronics runs through a technical question, and that question almost always waits in a queue. ### Sales teams The deal goes cold by the time an application engineer gets around to answering the question. ### Distributors and channel Specialists can answer a technical question, but there aren’t enough of them to cover a catalog this size. Why now ### Catalogs keep growing More SKUs, variants, and documentation per part every quarter. ### Hard to find talent An FAE or a good Sales Engineer is a mix of engineering and sales talent, which is hard to find. ### Modern buyers want to self-serve The technical evaluation is over before anyone picks up a phone. ### The AI is finally good enough Accurate on parametric data, which is the bar this industry needs. See if AI can work with your product documentation today. [Check your AI readiness](https://www.rapidflare.ai/resources/ai-readiness-report) What it does ## Task-specific agents From the moment a buyer searches for a solution, to the moment they need support after the sale, Rapidflare is the one source of truth. One knowledge graph underneath and five agents on top of it. Why it is accurate ## A general model pointed at a folder of PDFs will guess; this will not General models improvise when the data runs out. On a parametric spec, improvisation is a wrong part in a customer's hands. ### A curated knowledge graph Your datasheets, catalogs, BOMs, and support history, turned into one connected map of your products. Built once, and enriched continuously. ### Structured reasoning It figures out what’s being asked, plans its steps, and only pulls the knowledge that task needs. Complex inside, simple outside. ### Expert in the loop Your application engineers validate the data and the agents. Their corrections are permanent, not one-off. ### A source on every line Every claim traces to the document it came from. You can see each step the agent took to get there. 49% · AWS Textract 62% · Contextual AI 95% · Rapidflare // Document extraction accuracy, 2026 ### Extraction accuracy on technical documents Accuracy starts at extraction. If the spec table is read wrong, every answer downstream is wrong, no matter how good the model on top of it is. [Read the methodology](https://www.rapidflare.ai/methodology) Enterprise ## The agent is the easy part; this is the rest Everything that IT, security, and procurement, etc. will ask for before your team is allowed to use any of it. ### Enterprise-grade security Your documentation is isolated, encrypted, and never leaves your tenant. Five levels of Rapid Shield sit between your data and others. ### Built for teams One deployment, many audiences. Each hub gets its own agent and its own sources, without duplicating the knowledge behind it. ### You stay in control Configure what the agent will and will not say, without filing a ticket. Every answer is logged, so you can see what it is being asked and where your documentation is thin. · ### It plugs into what you already run Connect any enterprise system, then attach a workflow to any action the agent takes. Quotes, orders, CRM handoff, lead capture. · ### You get engineers, not a ticket queue A forward-deployed engineering team that builds the solution with you, and continuous accuracy evaluations so quality is measured, not assumed. [See all enterprise capabilities](https://www.rapidflare.ai/product/platform) Deploy anywhere ## Meet your people where they already work Nobody has to learn a new tool. The agent shows up in the surface they are already in, answering from the same knowledge graph. Impact ## Answer first, win the deal 1 min To answer a technical query Versus days 5 min To produce a proposal Versus weeks 30% Fewer L1 support calls Versus a growing backlog 1 day To ramp a new rep Versus weeks ### What would this be worth on your catalog? Move the two sliders. The full calculator adds deal size, win rate, and support cost, and gives you a number you can take to your CFO. [Open the ROI calculator](https://www.rapidflare.ai/resources/calculators) Sales reps and resellers**120** Technical questions per person per week**6** 2,322 Hours returned to the business each month Assumes 45 minutes lost per unanswered technical question, and 4.3 weeks per month. Pricing ## Three ways to start Plans are based on the size of your product catalog and the number of users. We scope each plan with you upfront, so you know exactly what's included. ### Basic One agent, one job. For a team proving the value on a focused slice of the catalog. - ✓Marketing site and full-screen deployment - ✓Conversation history and usage analytics - ✓Onboarding QA and initial accuracy tuning - ✓Email support Up to 3 sources 1 integration Quarterly accuracy report 5 customer success hours per month [Talk to sales](#cta) Most teams start here ### Professional The agent shows up where your people already work, and you control what it says. - ✓Embed in Slack, Zendesk, and partner portals - ✓Rich artifacts: comparison tables, proposal docs - ✓Admin tuning and controllable outcomes - ✓Content gap analysis and advanced analytics Up to 5 sources 2 integrations Monthly accuracy report 20 customer success hours, SSO, dedicated CSE [Talk to sales](#cta) ### Enterprise Many agents, many audiences, wired into the systems that run your business. - ✓Agent hubs, one per use case - ✓Workflow automation, lead capture, CRM handoff - ✓Human in the loop on high-stakes answers - ✓Bill of materials generation Unlimited sources Unlimited integrations Continuous accuracy evaluation 50+ customer success hours, FDE team [Talk to sales](#cta) Every plan · ✓Hallucination control · ✓Structured reasoning · ✓A source on every answer · ✓Multilingual · ✓Comparison across datasheets [Compare every feature →](https://www.rapidflare.ai/pricing) FAQ ## The questions you are about to ask We answered the questions that come up on every first call. Still have a question? Talk to someone who has deployed this in your industry. [Contact us](#cta) We benchmark 95% extraction accuracy on technical documents, against 62% for Contextual AI and 49% for AWS Textract, and every deployment ships with its own accuracy evaluation. When the data doesn’t support a confident answer (especially on parametric specs) the agent says so instead of guessing. Three things. Your documentation is structured into a knowledge graph rather than dumped into a vector index, so the agent retrieves facts. Structured reasoning constrains which knowledge it is allowed to use for each task, and every claim carries the source it came from. Because a general model improvises when the data runs out, and on a spec table that means a wrong part in a customer's hands. It also cannot tell you which of your 4,000 documents is the current one. The graph, the reasoning layer, and the human validation are the difference between a demo and something a rep will trust on a call. Your application engineers, in the admin dashboard. Their corrections are permanent, and on high-stakes answers like pricing you can require a human in the loop before anything reaches a customer. In an isolated tenant. Encrypted at rest and in transit, never pooled with another customer, and never used to train a model that anyone else touches. We are SOC 2 Type II, audited annually. Yes, and without filing an engineering ticket. Role-based access controls which sources each audience can reach, so a customer-facing agent and an internal one can run on the same graph while seeing different things. Competitor comparisons, pricing, and unreleased parts can each be switched off. They live in a hub with restricted access. Your internal teams can ask about them, the public agent on your website cannot see them at all. Days, not months. Send us a slice of your documentation, we ingest it and build the knowledge graph, and you see the agent answering your own questions on a 30 minute call. Full production deployment depends on how many sources you are connecting. Yes. We already run against Salesforce, SharePoint, Drive, Box, Zendesk, WordPress, and PIM systems, and the API lets you attach a workflow to any action the agent takes. Portal.io built their entire proposal product on it. No. The agent shows up in the surface they are already in: your website, Slack, Teams, the CRM record, email, the partner portal, or inside your own product. Same knowledge graph underneath all of them. It scales with the size of your catalog and the number of people using it. Every plan is scoped with our team first, so the number you see is the number you pay. Talk to sales and we will size it against your actual documentation. Your documentation stays yours. Isolated per customer. Never used to train anyone else's model. Audited annually, and every deployment is reviewed by a named customer success engineer. [SOC 2 Type II](https://www.rapidflare.ai/product/security) [Data isolation](https://www.rapidflare.ai/product/security#data-isolation) [Access control](https://www.rapidflare.ai/product/security#access-control) [Trust center](https://app.vanta.com/rapidflare.ai/trust/pu8d0fi1rb1eqr6m30zh3h) See it in action ## See it work on your product documentation Share a small sample of your documentation. We’ll build a custom agent so you can test real product questions with your own content. _01_ Tell us what you want to test We’ll discuss your use case and the questions you want the agent to handle. _02_ Get an agent built on your documentation We’ll set it up using the documentation you choose to share. _03_ Test it with dedicated engineering support A dedicated Forward Deployed Engineer works with you to evaluate and refine the agent. Full name Work email Company I'm looking for No confidential docs. No commitment. Prefer to assess your documentation first? [Check your AI readiness →](https://www.rapidflare.ai/resources/ai-readiness-report) --- # AI Agents Source: https://www.rapidflare.ai/product/agents > Specialized AI agents that understand your products, not just your documents. Each is grounded in your Product Intelligence and built around one workflow. Rapidflare AI Agents # AI Agents built on Product Intelligence Give customers, sales teams, support teams, and channel partners specialized AI experiences that understand your products, not just your documents. Rapidflare AI Agents are grounded in your product catalogs, specifications, technical documentation, relationships, and source evidence, so they can handle complex product workflows with the accuracy technical teams require. [See AI Agents in action](https://www.rapidflare.ai/contact) - Grounded in Product Intelligence - Source-backed answers - Built around one workflow at a time What are Rapidflare AI Agents? ## Specialized AI experiences, built on what your products really are Rapidflare AI Agents are specialized AI experiences designed to complete defined product workflows using your company's Product Intelligence. Instead of relying on a general-purpose model to interpret fragmented documents each time a question is asked, Rapidflare Agents work from a structured understanding of your products, specifications, applications, compatibility, alternatives, and technical evidence. Product Intelligence provides the understanding. AI Agents put that understanding into repeatable workflows. What can you do with AI Agents? ## Turn your most common product workflows into intelligent experiences 01 ### Product Selection Help people find the right product for their application. Guide customers, sales teams, and field engineers from a real-world requirement to the products that best fit it. Instead of forcing users through rigid parametric filters, the Agent can understand the application, ask clarifying questions, evaluate relevant specifications, and recommend suitable products with supporting evidence. Every cut is caused by a question, not by a filter the user had to know to set. Guided product discovery · Application-based selection · Catalog navigation · Product recommendations · Internal sales & FAE workflows [Explore Product Selection →](https://www.rapidflare.ai/product/rapid-product-selection) 02 ### Technical Support Give customers and support teams faster access to accurate technical answers. Answer product integration, configuration, troubleshooting, certification, and technical documentation questions using trusted product knowledge. Agents can operate as customer-facing support experiences or as internal tools for support engineers handling complex escalations. It answers what it can prove, and escalates what it cannot. Product support · Troubleshooting · Integration questions · Configuration guidance · Internal escalation support [Explore Technical Support →](https://www.rapidflare.ai/product/rapid-technical-support) 03 ### Competitive Cross-Reference Turn competitor part numbers into actionable product opportunities. Compare competitive products against your portfolio using technical specifications, applications, compatibility, and performance criteria. Help sales teams and customers identify the closest alternatives while showing the evidence behind the recommendation. The honest answer includes what does not match. Competitive replacement · Part cross-reference · Product comparison · Competitive positioning · Sales opportunity identification [Explore Competitive Cross-Reference →](https://www.rapidflare.ai/product/rapid-cross-reference) 04 ### Proposal Generation Turn product knowledge into faster, more accurate proposals. Bring together product specifications, approved technical content, previous responses, and supporting documentation to help teams prepare proposals and RFP responses faster. Nothing is invented. Every line traces to something already approved. RFP responses · Technical proposals · Product recommendations · Reusable approved answers · Proposal research [Explore Proposal Generation →](https://www.rapidflare.ai/product/rapid-proposals) 05 ### Sales Enablement Give every seller access to your best product knowledge. Rapid Sales helps sales teams, distributors, resellers, and channel partners answer product questions, compare alternatives, recommend products, and prepare for customer conversations, without relying on a small group of product experts. The people selling for you do not all work for you. Sales preparation · Product questions · Distributor enablement · Reseller support · New-hire ramp / time to competency [Explore Sales Enablement →](https://www.rapidflare.ai/product/capabilities) Why are Rapidflare AI Agents different? ## Generic AI knows how to answer; Rapidflare knows your products ### Grounded in Product Intelligence Every Agent is powered by the same structured understanding of your product portfolio, so it can reason across products, specifications, applications, compatibility, and relationships rather than simply searching individual documents. ### Source-backed answers Technical answers can be traced back to the product documentation and evidence behind them. That matters when an incorrect specification can lead to the wrong product recommendation, installation, design decision, or customer commitment. ### Built around a specific job Rapidflare Agents are designed around defined workflows rather than open-ended chat. A Product Selection Agent behaves differently from a Support Agent because the job, information required, and desired outcome are different. ### Built for complex products Rapidflare is designed for industries where catalogs contain thousands of SKUs, technical specifications determine product fit, and users often begin with an application rather than an exact part number. Measured in production [Read the case studies →](https://www.rapidflare.ai/customers/casestudies) [30% · Fewer Level 1 support queries · Global access-control leader](https://www.rapidflare.ai/customers/access-control) [99,000+ · Authorized dealer and integrator product questions supported · Cloud-managed video surveillance provider](https://www.rapidflare.ai/customers/alibi) [9,000+ · AI-assisted interactions in the first seven months · Security Industry Association](https://www.rapidflare.ai/customers/sia) How do Rapidflare AI Agents work? ## From Product Intelligence to a deployed workflow 1 ### Start with Product Intelligence Rapidflare connects catalogs, datasheets, product pages, application notes, technical documentation, and internal systems to build a structured understanding of your products. 2 ### Configure the workflow Define what the Agent needs to accomplish, from product selection and cross-reference to technical support, proposal generation, or sales enablement, configured around the users, product families, and questions that matter to your business. 3 ### Deploy where people need it Customers, sales teams, field application engineers, support teams, distributors, resellers, and channel partners, inside customer experiences, internal workflows, or existing systems. One Product Intelligence layer. Multiple Agents. ## You don't need a separate knowledge system for every AI use case The same Rapidflare Product Intelligence layer can power multiple specialized Agents across the organization. That means the answers stay grounded in the same product knowledge even when the user and workflow change. Where AI Agents matter most ## Built for teams working with complex technical products ### Semiconductors & electronic components Help customers and field teams navigate thousands of parts, specifications, packages, applications, and competitive alternatives. ### Physical security Guide product selection and technical support across cameras, video surveillance, access control, VMS, integrations, and compatibility requirements. ### Distribution & channel Give internal sales teams and reseller networks access to accurate product knowledge across large, multi-vendor catalogs. AI Agents or Forge? ## Two ways to put Product Intelligence to work Use AI Agents ### When the workflow is repeatable An Agent is best when you know the job you want the AI to perform repeatedly. - Recommend a product - Answer a support question - Cross-reference a competitor - Prepare a proposal - Help a distributor find the right product Use Forge ### When the work is open-ended Forge is designed for more complex, multi-step work where the task changes from request to request. - Research an entire competitive market - Build a customized presentation - Create enablement materials - Analyze a new product portfolio - Execute a multi-step research and creation workflow [Explore Forge](https://www.rapidflare.ai/product/forge) AI Agents operationalize Product Intelligence. Forge gives teams the freedom to work with it. FAQ ## Frequently asked questions What is an AI Agent for product companies? An AI Agent is a specialized AI experience designed to complete a defined product workflow, such as product selection, technical support, or cross-reference, using a structured understanding of your products rather than a general-purpose model reading fragmented documents. How are Rapidflare AI Agents different from chatbots? A chatbot answers open-ended questions from whatever text it can retrieve. A Rapidflare Agent is built around a specific job and grounded in Product Intelligence, so it reasons across specifications, applications, compatibility, and relationships, and every answer traces back to source evidence. What data can Rapidflare AI Agents use? Agents work from your Product Intelligence, built from product catalogs, datasheets, product pages, application notes, technical documentation, and internal systems. Who can use Rapidflare AI Agents? Customers, sales teams, field application engineers, support teams, distributors, resellers, and channel partners, inside customer-facing experiences, internal workflows, or existing systems. Put Product Intelligence into action ## Deploy specialized AI Agents that help your customers and teams get answers, not just documents Select products, answer technical questions, compare alternatives, and complete complex product workflows, grounded in your own product knowledge. [See Rapidflare AI Agents in action](https://www.rapidflare.ai/contact) --- # Capabilities Source: https://www.rapidflare.ai/product/capabilities > The full list of technical-sales jobs the agents do, each mapped to the agent that powers it and the team it serves. Product · the task index # Start from the task you have The agents are the engine's hands. Here is the full list of jobs they do, each mapped to the agent that powers it and the team it serves. [Agents](https://www.rapidflare.ai/product/agents) → [Platform](https://www.rapidflare.ai/product/platform) → Capabilities Task · What it does · Powered by · Sold to Cross-reference · Match any competitor part to your closest equivalent, ranked by compatibility. · Rapid Cross-Reference · [Sales](https://www.rapidflare.ai/team/sales) Learning · Turn your corpus into onboarding that cuts ramp time for new reps. · Rapid Learning · [Technical support](https://www.rapidflare.ai/team/support)[Marketing](https://www.rapidflare.ai/team/marketing) Product selection · Turn a vague need into the exact right part, with a defensible shortlist. · Rapid Selection · [Sales](https://www.rapidflare.ai/team/sales)[Technical support](https://www.rapidflare.ai/team/support) Proposal generation · Go from a set of requirements to a quote-ready bill of materials. · Rapid Proposals · [Bidding](https://www.rapidflare.ai/solutions/bidding) Recommendations · Surface the accessory or upgrade a design truly needs, grounded in compatibility. · Rapid Recommendations · [Sales](https://www.rapidflare.ai/team/sales) Technical support · Answer hard product questions across every source, with citations. · Rapid Support · [Technical support](https://www.rapidflare.ai/team/support) One capability, up close ## Cross-reference Match any competitor part to your closest equivalent, ranked by compatibility. Before A competitor SKU comes in and someone hunts through spec sheets to find the nearest match by hand. After The part is normalized across naming and units, ranked against your catalog, and returned as a side-by-side in seconds. Powered by **Rapid Cross-Reference** · sold to Sales This task rides on extraction, so the accuracy number is where it starts. Extraction accuracy, our benchmark - Rapidflare · · 95% - Contextual AI · · 62% - AWS Textract · · 49% [How we measured this](https://www.rapidflare.ai/methodology) ## Agents, capabilities, solutions: how they fit Each capability points inward to the [agent](https://www.rapidflare.ai/product/agents) that powers the job, and outward to the [solution](https://www.rapidflare.ai/team/sales) that sells it to a team. Same six agents, two views: the object view on Agents, the task view here. ## Tell us the task and we will show you the agent that does it [Book a demo](https://www.rapidflare.ai/contact) --- # Deployment model Source: https://www.rapidflare.ai/product/deployment > Days, not months. A slice of your documentation becomes a working agent on your own parts this week, with evals before go-live and an engineer on the rollout. Deployment model # Live on your catalog in days, not months No model training, no taxonomy project, no six-month integration. Send a slice of your documentation, and this week you are asking an agent hard questions about your own parts. [Start with a product family](https://www.rapidflare.ai/contact) The first week ## From a folder of PDFs to an agent you can interrogate Day 1 ### Send a slice of your documentation A product family is enough: datasheets, application notes, whatever you have. No cleanup pass required, the extraction is built for documents as they are. Days 2 to 3 ### We ingest it and build the graph Specs become typed facts with units, revisions, and product relationships. The pipeline has processed catalogs past the million-document mark, with per-file retries, so one corrupt PDF does not stall the week. This week ### You grill the agent on a 30 minute call It answers your questions about your own parts. That call is the real evaluation, and plenty of customers bring their hardest support tickets to it. Before go-live ### Evals, controls, and sign-off Your evaluation suite runs on your documents and your real questions. Role-based source controls decide what each audience can see. You watch the scores before your customers see the agent. Forward-deployed engineers ## Our team embeds with yours to get it right ### Embedded, not ticketed A forward-deployed engineer runs the rollout with you: connects the sources, tunes the evals, and stays on it until the agent earns your trust. ### No model training step The graph is built from documents you already have. There is no fine-tuning project, no taxonomy workshop, and nothing for your team to label. ### Your effort is pointing, not building Most of what we need from your team is knowing where the documentation lives and reviewing eval results. After go-live ## Hands-off for your team, not for ours ### Sources stay current Connectors watch SharePoint, Drive, your PIM, and the rest, so the agent answers from what your systems say today. ### Evals keep running Documentation changes, the suite re-runs, and regressions surface before customers do. ### Scope grows on evidence Start with one audience and one workflow, widen to the channel when the scores say so. ## Looking for pricing, a benchmark, or a customer reference? [Get in touch](https://www.rapidflare.ai/contact) [How the platform works →](https://www.rapidflare.ai/product/platform) --- # Forge Source: https://www.rapidflare.ai/product/forge > Grounded AI for complex product work. Forge gives your teams autonomous AI, grounded in your Product Intelligence, that takes a task from objective to result. Rapidflare Forge # Grounded AI for complex product work Forge gives your teams the power of autonomous AI, grounded in your company's products, customers, technical knowledge, and competitive context. [See Forge in action](https://www.rapidflare.ai/contact) - Grounded in Product Intelligence - Built for multi-step work - Finished deliverables What is Forge? ## Rapidflare's AI environment for complex, open-ended work Unlike an AI Agent built to perform one defined workflow, Forge can work across files, research, data, code, and multiple steps to take a task from an initial goal to a finished deliverable. And because Forge is built on Rapidflare Product Intelligence, its work can be grounded in your company's actual products, technical documentation, applications, customers, and competitive knowledge. General-purpose AI starts with a prompt. Forge starts with your Product Intelligence. From answers to outcomes ## Where most AI tools stop at an answer, Forge keeps going until the work is done Not just answer the next question. Do the work. What can Forge do? ## Turn Product Intelligence into finished work 01 ### Research & competitive analysis Go beyond a single product comparison. Forge can research competitors, evaluate product portfolios, analyze applications and positioning, and bring internal product knowledge together with external information. Internal knowledge and external research, in the same pass. - Analyze a competitor's product portfolio - Build detailed competitive comparisons - Identify product positioning opportunities - Research target markets and applications - Create competitive battlecards How Forge runs it Research competitors → compare products → analyze technical differences → identify positioning → build the battlecard 02 ### Presentations & sales materials Turn product knowledge, technical information, customer context, and research into finished sales and enablement materials. The deck starts at slide twelve, not slide zero. - Customer presentations - Prospecting decks - Product launch decks - Competitive presentations - Executive briefings - Sales enablement materials How Forge runs it Research the account → understand the application → match relevant products → find supporting evidence → create the presentation 03 ### Channel enablement & training Create materials that help distributors, resellers, field teams, and partners understand and sell complex products. Your best explanation, teachable at channel scale. - Product training guides - FAE enablement materials - Distributor playbooks - Step-by-step technical guides - Product family training - Partner-specific content How Forge runs it Understand the product family → identify selection criteria → structure the training → produce the final material 04 ### Personalized GTM content Create relevant outreach and sales content using actual product fit rather than generic personalization. Personalized by product fit, not by first name. - Account-specific outreach - Event and tradeshow campaigns - Prospect research - Product-specific messaging - Account-specific value propositions - Sales prospecting materials How Forge runs it Research the account → map product fit → draft the message → tailor it per account 05 ### Product & technical content Turn trusted product knowledge into content without starting every project from a blank page. Never a blank page, and never an uncited claim. - Product positioning - Launch content - Technical comparisons - Press materials - Product briefs - Internal documentation How Forge runs it Pull the trusted facts → structure the piece → draft with citations → hand off for review 06 ### Code & integrations Work from your real technical documentation to create code and workflows connected to your systems. Written against your documentation, tested before you see it. - API integrations - Scripts - Data workflows - Internal tools - Product-data utilities - Workflow automation How Forge runs it Read your documentation → write the integration → test against real data → deliver working code The difference is grounded autonomy ## Powerful AI is useful, and powerful AI that knows your products is more useful General-purpose AI can create impressive work. But when the task depends on technical specifications, product relationships, competitive positioning, internal knowledge, or customer-specific context, generic output is not enough. Forge combines autonomous AI capabilities with your company's Product Intelligence. That means the work it produces can be grounded in: Your product catalog Technical specifications Datasheets Product relationships Applications and use cases Competitive information Internal documentation Customer-specific context Forge doesn't just know how to do the work. It has the product context required to do the work well. How does Forge work? ## From objective to deliverable 1 ### Give Forge an objective Start with the work you want completed, not a sequence of individual prompts. 2 ### Forge works across the task Forge can break complex objectives into multiple steps and work across the information required to complete them, all as part of the same workflow. Research · Files · Product knowledge · Analysis · Content · Code 3 ### Product Intelligence keeps the work grounded Forge has access to the same trusted Product Intelligence that powers Rapidflare, so the work reflects what your company sells, supports, and knows, rather than relying solely on general model knowledge. 4 ### Get a finished deliverable The outcome isn't another chat response. It can be the thing you needed. A presentation · A competitive analysis · A training guide · A campaign · A spreadsheet · Code Forge vs. AI Agents ## Two ways to put Product Intelligence to work AI Agents ### For repeatable workflows Use AI Agents when the job is known and happens repeatedly. - Help a customer select a product - Answer a technical support question - Cross-reference a competitor part - Generate a proposal - Help a distributor navigate the catalog Defined workflow → repeatable experience [Explore AI Agents →](https://www.rapidflare.ai/product/agents) Forge ### For complex, open-ended work Use Forge when the objective is clear, but getting there requires research, reasoning, creation, tools, and multiple steps. - Research an entire competitive category - Create a customized customer presentation - Build channel training materials - Analyze a new market - Create code against your APIs - Execute a multi-stage GTM project Defined objective → autonomous execution Built for teams, not just individual productivity ## Forge brings Product Intelligence into the work performed across your organization ### Sales Create account research, presentations, competitive materials, and prospect-specific content. ### Product marketing Research markets, build positioning, create launches, and turn technical product knowledge into campaigns. ### Field application engineers Create technical materials, analyze applications, and build customer-specific enablement. ### Channel teams Generate distributor training, reseller materials, and partner-specific product guidance. ### Customer success Analyze requirements, build customer materials, support proposals, and turn technical knowledge into usable deliverables. Why Forge for complex technical products? ## Generic AI becomes less reliable as product complexity increases A semiconductor, security, electronics, or industrial technology company may need an AI system to reason across thousands of products, technical specifications, applications, documentation, and competitive relationships before it can create useful work. That context is what Rapidflare already understands. Product Intelligence gives Forge the facts. Forge turns those facts into work. Measured in production [Read the case studies →](https://www.rapidflare.ai/customers/casestudies) [30% · Fewer Level 1 support queries · Global access-control leader](https://www.rapidflare.ai/customers/access-control) [99,000+ · Authorized dealer and integrator product questions supported · Cloud-managed video surveillance provider](https://www.rapidflare.ai/customers/alibi) [9,000+ · AI-assisted interactions in the first seven months · Security Industry Association](https://www.rapidflare.ai/customers/sia) FAQ ## Frequently asked questions What is Rapidflare Forge? Forge is Rapidflare's AI environment for complex, multi-step work. It combines autonomous AI capabilities with Rapidflare Product Intelligence so teams can research, analyze, create, and execute using trusted company and product knowledge. How is Forge different from a general-purpose AI assistant? General-purpose AI primarily works from the information provided in a conversation and its general model knowledge. Forge is designed to work across multi-step tasks while using Rapidflare Product Intelligence to ground the work in your company's products, technical documentation, applications, and other trusted knowledge. How is Forge different from Rapidflare AI Agents? AI Agents are designed around repeatable product workflows such as product selection, technical support, and cross-reference. Forge is designed for open-ended objectives where the path to the outcome can involve multiple steps, tools, research, analysis, and creation. What can Forge create? Forge can support work including presentations, competitive analysis, product and sales content, channel training materials, research, technical documentation, code, API integrations, and other complex deliverables. Who is Forge built for? Forge is designed for teams working with complex product knowledge, including sales, product marketing, field application engineering, channel, customer success, and other technical or go-to-market organizations. Give your teams AI that knows your products ## Bring the flexibility of autonomous AI together with the trusted Product Intelligence behind your company From research to analysis to finished work. [See Forge in action](https://www.rapidflare.ai/contact) --- # Forward Deployed Engineering Source: https://www.rapidflare.ai/product/forward-deployed-engineering > Every customer gets a Forward Deployed Engineer for the life of the partnership: someone who turns your requirements into working AI and stays on after launch. Forward Deployed Engineering # AI software is only useful when it works for your business That is why every Rapidflare customer gets a Forward Deployed Engineer. Your products, data, workflows, systems, and users are different. Instead of asking your team to figure out how to adapt Rapidflare to them, we assign a Forward Deployed Engineer who works alongside your team from onboarding throughout the entire partnership. They help turn your requirements into working AI experiences, from the first deployment to everything you want to build next. [Talk to our team](https://www.rapidflare.ai/contact) - Included with every Rapidflare engagement - No separate professional services contract required More than implementation support ## Most implementations end at the same point; Rapidflare doesn't Most implementations Product gets deployed_→_ Implementation team leaves_→_ Your team is on its own Rapidflare Onboarding_→_ Deployment_→_ Your FDE stays involved_→_ Throughout the partnership Your Forward Deployed Engineer builds context around your deployment, product knowledge, technical environment, requirements, and how your users are using Rapidflare day to day. So when something needs to change, improve, integrate, or expand, you have an engineer on the Rapidflare side who already understands the context. What does your Forward Deployed Engineer do? ## One job: make Rapidflare work the way your business runs That can mean helping across the entire lifecycle of your deployment. ### Knowledge and data Connect and structure the product information your agents need across documentation, catalogs, websites, knowledge bases, and internal systems. ### Agent configuration Configure Rapidflare around your products, users, workflows, terminology, and business requirements. ### Technical implementation Turn product and business requirements into the appropriate Rapidflare configuration and technical implementation. ### Integrations Work through the technical requirements needed to connect Rapidflare with your existing systems and deployment environment. ### Evaluation and debugging Investigate incorrect or incomplete answers, trace problems to their source, and work with the broader Rapidflare team to resolve them. ### New requirements When your business needs something the original deployment did not anticipate, help translate that requirement into the right configuration, workflow, integration, or product capability. ### Continuous optimization Use production feedback and usage patterns to identify opportunities to make the experience more useful over time. Where the work is divided ## Your team brings the domain expertise and we handle the AI engineering Your people know your products, customers, systems, and business better than anyone. We do not want them spending their time becoming experts in AI infrastructure or learning how to operate another platform. Your team helps us answer questions like: Your team answers · · Your FDE builds “What should the system accomplish?” **Agent configuration**Scoped to your users, terminology, and workflows “Which information should it rely on?” **Knowledge ingestion**Your sources, structured into the graph “What does a correct answer look like?” **Evaluation and QA**An eval suite built to your standard “How should this fit into our existing workflow?” **Integrations**Wired into the systems you already run “What do our users need next?” **New workflows**Requirements turned into the next release Five answers from your team. A working system from your FDE. Continuity, not a cold start ## One engineer who already knows your environment A new requirement six months after launch should not mean starting from zero with someone reading your support ticket for the first time. Your Forward Deployed Engineer already understands the context behind your Rapidflare deployment. · Kickoff Learns your products, sources, and systems · Launch Knows what was built, and why it was built that way · Month three Sees how real users use it, and what they ask next · Month six Picks up your new requirement without a cold start What you need_→_ What gets built_→_ How it performs_→_ What gets improved next You do not lose that context once onboarding is over. Launch is not the handoff ## It is the beginning of the working relationship Once real users begin interacting with Rapidflare, new opportunities emerge. They ask unexpected questions · They expose gaps in product information · They reveal new workflows worth supporting · Your catalog changes · Your company launches new products · Teams find new ways to use AI · New systems need to be connected · Your requirements evolve Your Forward Deployed Engineer remains part of that process, helping your Rapidflare deployment evolve alongside your business. From requirement to implementation ## Someone already responsible for understanding both sides of the problem Your team should not have to decide whether every new AI requirement warrants another internal engineering project. Your business requirement · What are you trying to accomplish? Your product and data · What information, systems, and domain knowledge does it depend on? Rapidflare · How should the platform, agent, workflow, or integration be configured? Production · How does it work for real users? Feedback · What needs to be improved next? Your FDE helps maintain that loop throughout the partnership: feedback flows straight back into the next requirement. What this means for your team ## Six things that change once an engineer is already on your requirements ### Less internal engineering work You do not need to build a team responsible for configuring and operating your Rapidflare deployment. ### Faster path from requirement to implementation When your team identifies a need, there is already someone technically responsible for helping turn it into a working solution. ### Less vendor handoff The technical relationship does not disappear once the initial implementation is complete. ### More continuity Your engineer builds knowledge about your deployment over time instead of forcing your team to repeatedly explain the same context. ### Continuous improvement Production feedback can become product improvements rather than simply accumulating in a dashboard or support queue. ### More value from the platform As your requirements evolve, your Rapidflare deployment can evolve with them. Not professional services ## Forward Deployed Engineering is not scoped around a project Typical professional services Project starts_→_ Hours consumed_→_ Project ends_→_ New requirement means new scope Your FDE at Rapidflare There during onboarding · There when you deploy · There when users start generating feedback · There as new requirements emerge Forward Deployed Engineering is part of Rapidflare Not an add-on. Not a limited onboarding package. Not a block of professional-services hours you need to purchase every time something changes. Every Rapidflare customer gets a Forward Deployed Engineer throughout the partnership, included as part of the engagement. Because enterprise AI should not require your company to become an AI engineering company just to make it work. FAQ ## Frequently asked questions Is Forward Deployed Engineering an additional paid service? No. A Forward Deployed Engineer is included as part of every Rapidflare customer engagement. There is no separate professional services package required to work with your FDE. How long does our Forward Deployed Engineer stay involved? Throughout your partnership with Rapidflare, not just during onboarding or the initial implementation. Your FDE continues working with your team as your deployment and requirements evolve. Does this replace our own engineering team? No. Your team may still need to provide access, technical context, or involvement for systems you control. But you do not need to dedicate internal engineers to becoming Rapidflare experts or operating the AI system itself. Your FDE owns the Rapidflare side of that technical relationship. What happens if we have a new requirement after launch? Bring it to us. Your Forward Deployed Engineer can work with your team to understand the requirement and determine how best to address it through configuration, data, integrations, workflows, or Rapidflare's product capabilities. Is this just technical support? No. Technical support is primarily reactive: something goes wrong, and someone helps resolve it. Forward Deployed Engineering is broader. Your FDE works proactively with your team to deploy, improve, adapt, and expand how Rapidflare is used across your organization. What kinds of people will our FDE work with? That depends on the deployment. They may work with your product experts, engineering or IT teams, customer support leaders, sales teams, product managers, or other stakeholders involved in the use case, bridging your business and product requirements with the technical Rapidflare implementation. Your requirements should not end in a support queue ## Put an engineer on them Every Rapidflare engagement includes a Forward Deployed Engineer who works alongside your team from onboarding through everything that comes next. Not just to get Rapidflare live: to keep making it work for your business. [Talk to us about your requirements](https://www.rapidflare.ai/contact) --- # Integrations Source: https://www.rapidflare.ai/product/integrations > Connect your product stack with 950+ integrations across 30 categories: knowledge bases, storage, CRM, ERP, support, commerce, developer tools, and native MCP. Rapidflare Integrations # Connect your product stack with 950+ integrations Your product knowledge already lives across dozens of systems. Rapidflare connects the tools where that knowledge lives and brings it into Product Intelligence. [Browse integrations](#directory) [Request an integration](https://www.rapidflare.ai/contact) **950+** integrations _·_ **30** categories _·_ Native **MCP** support Featured integrations ## Works with the tools your teams already use Rapidflare plugs into the tools your product, sales, support, and engineering teams already run. Salesforce HubSpot SAP S/4HANA NetSuite ServiceNow SharePoint Google Drive Confluence Notion Slack Microsoft Teams Jira GitHub Zendesk Shopify Workday [Explore all integrations →](#directory) Integration directory ## Find the integration you need Search more than 950 available integrations or browse by category. Search integrations: Salesforce, SharePoint, Slack, SAP… Popular categories [Knowledge-base](#directory)[Storage](#directory)[CRM](#directory)[ERP](#directory)[Support](#directory)[CMS](#directory)[E-commerce](#directory)[Dev-tools](#directory)[MCP](#directory)[Communication](#directory)[Analytics](#directory)[Productivity](#directory) [View all categories ↓](#directory) Connect the knowledge behind your products ## Product knowledge rarely lives in one place A datasheet lives in SharePoint. Product docs live in Confluence. Sales context is in Salesforce, support tickets in Zendesk, and product data in whatever ERP or commerce platform runs the business. ### Knowledge & documents Where technical and product knowledge is created and maintained. Google Drive · SharePoint · Confluence · Notion · OneDrive · Box · Dropbox · Coda · Guru · Glean · Document360 · and more ### Sales & customer context Bring customer and commercial context into the same environment as your product knowledge. Salesforce · HubSpot · Gong · Attio · Intercom · Zendesk · and more ### Product & business systems Pull together the systems containing product, operational, commerce, and business information. SAP S/4HANA · NetSuite · ServiceNow · Shopify · QuickBooks · Sage Intacct · and more ### Engineering & collaboration Reach into the places where technical teams build and work. GitHub · Jira · Linear · Slack · Microsoft Teams · and more Model Context Protocol ## Connect AI to the tools where work happens Rapidflare supports native MCP integrations across a growing ecosystem of applications, so any Rapidflare agent can reach into your other tools and systems directly. Native MCP connections include tools such as Amplitude · Asana · Attio · Canva · Cloudflare · Google Calendar · HubSpot · Linear · Notion · Sanity · Slack · Supabase · Vercel · WordPress.com · and more Rapidflare also supports a generic OAuth2 MCP server option for connecting additional MCP-compatible systems. [Browse MCP integrations →](#directory) What is MCP? ### A standard way for AI to reach your tools MCP (Model Context Protocol) provides a standardized way for AI systems to connect with external tools and services. For Rapidflare, that means AI doesn't have to stop at answering questions about your product knowledge. Connected tools can become part of the workflows your teams execute. More than another data sync ## Integrations make Product Intelligence more useful Rapidflare doesn't copy every piece of information into another system. It connects the context it needs to understand your products and help people act on it. ### Product knowledge Bring together information such as: - Product catalogs - Datasheets - Technical specifications - Application notes - Internal documentation - Product pages ### Business context Connect information such as: - Customer accounts - Opportunities - Orders - Support history - Product usage - Operational information ### Tools and workflows Connect the systems where teams get work done: - CRM - Support - Communication - Development - Productivity - Commerce - Analytics Your systems remain the sources, while Rapidflare becomes the intelligence layer across them. How integrations work with Rapidflare ## Connect once, then put the knowledge to work across the platform 1 ### Connect your systems Choose the systems containing the product, technical, customer, or operational information relevant to your business. 2 ### Build richer Product Intelligence Rapidflare weaves that context into its understanding of your products, how they relate to each other, and how they’re used. 3 ### Activate it across Rapidflare Use connected knowledge through: **Product Intelligence**Understand your products and the context around them. **AI Agents**Power repeatable workflows such as selection, support, and cross-reference. **Forge**Research, analyze, create, code, and execute complex work. One intelligence layer across your stack ## Your product knowledge doesn't need to move to become useful Keep the systems your teams already rely on. Give people and AI one trusted way to work across it. 950+ integrations. One Product Intelligence layer. FAQ ## Frequently asked questions How many integrations does Rapidflare support? Rapidflare supports more than 950 integrations across 30 categories, including knowledge bases, storage, CRM, ERP, support, CMS, commerce, developer tools, communication platforms, analytics, MCP-compatible services, and more. Does Rapidflare support MCP? Yes. Rapidflare supports native MCP integrations across a growing collection of services as well as a generic OAuth2 MCP server option for additional MCP-compatible systems. What knowledge-base integrations does Rapidflare support? Rapidflare supports knowledge and document platforms including Google Drive, SharePoint, Confluence, Notion, OneDrive, Box, Dropbox, Coda, Guru, Glean, Document360, and others. Can Rapidflare connect to CRM and ERP systems? Yes. Rapidflare supports CRM and enterprise systems including Salesforce, HubSpot, NetSuite, SAP S/4HANA, ServiceNow, and many others. Do I need to replace my existing systems? No. Rapidflare connects to the systems where your information already lives, those stay your source systems, and Rapidflare adds an intelligence layer on top. What if I don't see the integration I need? Talk to the Rapidflare team about the system or data source you need to connect. One layer across everything you already run ## Bring your product knowledge, customer context, and business systems into one place [Browse 950+ integrations](#directory) [Request an integration](https://www.rapidflare.ai/contact) --- # Hands-off onboarding Source: https://www.rapidflare.ai/product/onboarding > You signed, and here is what happens next: five steps from signature to production, a dedicated Forward Deployed Engineer, and no work landing on your team. Onboarding and handoff # You signed, and here is what happens next This is the page to send your team. It walks through how Rapidflare takes you from a signed deal to a production AI experience: what we need from you, what we handle, and who you will be working with along the way. From your kickoff call onward, a dedicated Forward Deployed Engineer works alongside your team to turn requirements into a working deployment, so nobody on your side is left guessing what comes next. [Schedule your kickoff call](https://www.rapidflare.ai/contact) No prep required for the kickoff call. We will tell you what to bring. - A dedicated Forward Deployed Engineer - End-to-end onboarding - Ongoing optimization included - Enterprise-ready security 5 steps · From handoff to production 1 dedicated FDE · Assigned at kickoff 950+ · Systems Rapidflare connects to Teams who have been through this handoff Rolling Wireless · Alibi Security · Taoglas > “The level of engagement and responsiveness from the team stood out. They collaborated with us to implement additional features that enhanced the solution beyond the original scope.” What to tell your team ## The first question you will get is “who has to build this?” Here is the honest answer, and the one worth relaying: introducing enterprise AI can easily become another internal implementation project. This one is built not to. The work that exists · Who it falls on Data needs to be connected Rapidflare Knowledge needs to be structured Rapidflare Agents need to be configured Rapidflare Answers need to be evaluated Rapidflare Edge cases need to be investigated Rapidflare Integrations need to work Rapidflare Feedback needs to be monitored Rapidflare And someone needs to keep improving all of it once real users arrive Rapidflare, ongoing Rapidflare is designed so that work does not fall on your team. Our customer success and engineering teams manage the process end to end, from knowledge ingestion and configuration through testing, launch, and ongoing optimization. And every Rapidflare customer works with a Forward Deployed Engineer from onboarding throughout the partnership. Your handoff, step by step ## Five steps from signature to production, and your team owns one line in each 1 ### Start with the knowledge you already have You do not need to reorganize your product information before working with Rapidflare. Start with the sources your teams already use. That might include Product catalogs · Datasheets and PDFs · Technical documentation · Websites and URL lists · Knowledge bases · SharePoint · Google Drive · Confluence · YouTube content · Internal product information Your team Point us to the relevant sources and tell us what matters. Rapidflare Ingest, structure, configure, and prepare that knowledge for your AI experience. 2 ### We configure the experience around your business You are not handed a generic agent and asked to configure it yourself. We work with you to understand who will use the agent, what they need to accomplish, which products and knowledge it should cover, how it should behave, what a good answer looks like, and where the experience needs to be deployed. Rapidflare then handles the underlying configuration, from product coverage and instructions to starter prompts and deployment requirements. Your team Give us business and product context. Rapidflare Turn it into the working experience. 3 ### We test before your users depend on it Before broader rollout, the agent goes through evaluation and testing. We look at real questions, answer quality, positive and negative feedback, knowledge gaps, product-data issues, and edge cases. When something does not work, our job is not simply to record a bad answer. We investigate why it happened and work on the underlying issue. Your team Bring in domain expertise when a product or business judgment is required. Rapidflare Run evaluation, investigate issues, make improvements, and prepare the experience for launch. 4 ### We help take it live Once the experience is ready, Rapidflare works with your team on deployment: the website experience, internal environment, integration, workflow, or other surface your use case needs. Your Forward Deployed Engineer stays close to the technical requirements, so your team does not need to become experts in deploying or configuring Rapidflare. Your team Review and approve. Rapidflare Help get it into production. 5 ### Launch is not where our work stops Real users will ask questions no test suite predicted. That is useful. Once your agent is live, Rapidflare continues to monitor how it performs and works with your team to improve it. Your deployment keeps learning from what happens in production. That can include Usage and feedback monitoring · Performance reporting · Investigation of incorrect or incomplete answers · Product and catalog corrections · Knowledge-source updates · Starter-prompt optimization · New product coverage · New workflows and use cases · Integration improvements Your team Tell us what looks right, what does not, and what matters most. Rapidflare Monitor, investigate, and keep the agent improving. Want to walk your team through this before the kickoff call? Bring this to your kickoff meeting ## What we need from your team: less than you might expect You bring · · Rapidflare does the rest with it **Access**Show us where the relevant product knowledge lives. **Knowledge ingestion**Connect and process the information your AI experience needs **Context**Tell us who the experience is for and what those users need to accomplish. **Agent configuration**Configure Rapidflare around your products, users, terminology, and workflows **Domain expertise**Help us with questions only your product or business experts can answer. **Evaluation and QA**Test responses and investigate problems before and after launch **Feedback**Tell us what looks right, what does not, and what matters most. **Monitoring and optimization**Review usage and keep the experience improving once users arrive **Approval**Decide when you are comfortable putting it in front of users. **Deployment**Work through production and integration requirements with your team No line for your team at all: **technical implementation**, **debugging**, and the Rapidflare-side engineering in between. You do not do this alone ## Every Rapidflare customer gets a Forward Deployed Engineer Your Forward Deployed Engineer works alongside your team from onboarding throughout the partnership. They become familiar with your deployment, knowledge sources, technical environment, and requirements, and help turn what your business needs into a working Rapidflare experience. So when something needs to be configured, investigated, integrated, expanded, or improved, your team is not left figuring it out alone. [Meet your Forward Deployed Engineer](https://www.rapidflare.ai/product/forward-deployed-engineering) Forward Deployed Engineering is included as part of every Rapidflare engagement. Bring your team along ## The questions you will get internally, and what to tell them You are not buying software and being handed an implementation guide. You are getting a team that helps put it into production. Here is how to explain that to the people who will ask. IT and security “Is this another system we have to operate and secure?” No. Rapidflare owns the Rapidflare-side configuration, evaluation, and optimization; your team is not becoming an AI operations team. You will need to grant access to the relevant systems and weigh in on integrations, nothing more. Product and domain experts “How much of my time does this take?” Only the parts only you can answer. We bring your experts in for product and business judgment calls, not to run the system day to day, so they stay focused on product. Leadership and sponsor “What happens after launch: does this stall out?” It does not. Production usage gives us new information to evaluate and opportunities to improve, and your Forward Deployed Engineer stays engaged. Launch is a milestone, not the finish line. Built around what you already have ## Your product knowledge does not need to live in one perfectly organized repository first We meet your product knowledge where it is and work with your team from there. Documents Product catalogs · Datasheets and PDFs · Technical documentation · Internal product information Systems SharePoint · Google Drive · Confluence · Knowledge bases Web and media Websites and URL lists · YouTube content [See all 950+ integrations →](https://www.rapidflare.ai/product/integrations) What happens after launch? ## We stay involved Products change. Documentation changes. Customers ask new questions. Teams discover new use cases. New integrations become important. And occasionally, something does not work the way it should. Your relationship with Rapidflare does not turn into a support queue at that point. Our customer success team and your Forward Deployed Engineer continue working with you to understand what is happening, investigate issues, and evolve the experience. Launch is a milestone, not a handoff. Questions your team will ask ## Anticipate these before the kickoff call Do we need to clean up all our documentation before we start? No. Start with the product information you already have. Part of the process is understanding your existing knowledge sources and identifying the gaps, ambiguities, or inconsistencies that matter to the AI experience. Will our product or engineering team need to build the agent? No. Rapidflare handles the core ingestion, configuration, evaluation, and ongoing optimization work. Your experts provide product and business context where their judgment is valuable. Do we need to dedicate an engineer to Rapidflare? You may need technical involvement for access to systems your team controls or for certain integrations. But you do not need an internal engineer whose job is to learn how to operate Rapidflare. A Forward Deployed Engineer is included with every Rapidflare engagement and works with your team throughout the partnership. How involved does our team need to be? We deliberately focus your involvement on the areas where only your organization can provide the answer: your priorities, your product expertise, your systems, your approval. Rapidflare handles the operational work around those decisions. How do we know when the experience is ready? We evaluate the experience before broader rollout and work through issues identified during testing. Your team gets to review the experience and provide feedback before putting it in front of a wider audience. What happens when our product information changes? Knowledge management does not stop at launch. Rapidflare works with customers to keep their knowledge coverage and AI experience evolving as their products and information change. What happens if the agent gives a bad answer? We investigate it. Our team can review the underlying interaction, determine what caused the problem, and address issues in the knowledge, retrieval, configuration, or agent behavior. Ready for kickoff ## Bring us your product knowledge and we will take it from there From existing documentation to a production AI experience, without turning it into another major implementation project for your team. [Schedule your kickoff call](https://www.rapidflare.ai/contact) --- # Platform Source: https://www.rapidflare.ai/product/platform > The four-layer engine that turns your documents into knowledge-powered agents, with 95% extraction accuracy. Product · the engine # Most AI guesses, then sounds confident; ours is built to know, and to prove it Four layers turn the latent information in your documents into knowledge-powered agents you can stake a deal on. If Agents is "show me," Platform is "prove it." [Agents](https://www.rapidflare.ai/product/agents) → Platform → [Capabilities](https://www.rapidflare.ai/product/capabilities) 1. 01 · AI-ready extraction 2. 02 · Knowledge graphs 3. 03 · The harness 4. 04 · Explainable AI One chain, four steps. Latent information in, knowledge-powered agents out, and every answer traces back to the source. Layer 01 ## AI-ready extraction Can it read my documents, tables, and drawings, warts and all? Extraction is the foundation: if the engine cannot read the datasheet, nothing downstream matters. This is where the accuracy number is earned, so the benchmark lives right here. Extraction accuracy, our benchmark - Rapidflare · · 95% - Contextual AI · · 62% - AWS Textract · · 49% [How we measured this](https://www.rapidflare.ai/methodology) Layer 02 ## Knowledge graphs Does it understand my products, or just retrieve matching text? The extracted facts become a graph of your products and how they relate. That is why answers are precise and relational, not chunk-retrieval guesswork. This is the answer to the "isn’t this just RAG" question. Layer 03 ## The harness How does knowledge turn into work my team can use? The harness moves the story from knowledge to action: it lets an agent take steps, call your systems of truth, and complete a task, which is what makes these agents and not a search box. Layer 04 ## Explainable AI Can I trust the answer, and see why? Every answer traces back to its source, with the reasoning shown and citations inline. Explainability is the trust payoff of the whole pipeline, and the reason you can stake a deal on it. The engine, measured in production [Read the case studies →](https://www.rapidflare.ai/customers/casestudies) [30% · Fewer Level 1 support queries · Global access-control leader](https://www.rapidflare.ai/customers/access-control) [99,000+ · Authorized dealer and integrator product questions supported · Cloud-managed video surveillance provider](https://www.rapidflare.ai/customers/alibi) [9,000+ · AI-assisted interactions in the first seven months · Security Industry Association](https://www.rapidflare.ai/customers/sia) Enterprise ## The controls your security team will ask about - ### SOC 2 Type II Audited controls, independently verified. - ### Your data stays yours Grounded in your documentation, never used to train shared models. - ### Deploy where you work Website, Slack, CRM, email, and more, stood up by our engineers. ## Bring a document that usually breaks AI [Book a demo](https://www.rapidflare.ai/contact) [Can it do my task? See Capabilities →](https://www.rapidflare.ai/product/capabilities) --- # Product Intelligence Source: https://www.rapidflare.ai/product/product-intelligence > Turn fragmented product data and technical knowledge into a trusted intelligence layer that understands your products, specs, relationships, and applications. Rapidflare Product Intelligence # Product Intelligence for complex technical products Turn fragmented product data and technical knowledge into a trusted intelligence layer that understands your products, specs, relationships, and applications. [See Rapidflare in action](https://www.rapidflare.ai/contact) - Source-backed answers - Built for complex catalogs - Grounded in your product data What is Product Intelligence? ## A structured understanding of your products This includes their specifications, capabilities, relationships, applications, compatibility, alternatives, and supporting technical evidence. Rapidflare builds this intelligence from product catalogs, datasheets, BOMs, product pages, application notes, technical documentation, and internal systems. The problem ## Your company has product information; what it lacks is product understanding Technical product companies already have enormous amounts of product information. The challenge is that it lives across datasheets, catalogs, product pages, application notes, support documentation, internal systems, and the people who know the products best. Finding the right document doesn't necessarily answer the question. Datasheets · Catalogs · Application notes · BOMs · Support documentation · Product pages · Internal systems · Institutional knowledge What can Product Intelligence understand? ## Understand the relationships behind your product portfolio ### Products & specifications Understand individual products, families, and the technical attributes that define them. ### Applications Connect customer requirements and use cases to products that fit those needs. ### Product relationships Understand how components, accessories, systems, and product families relate. ### Compatibility Identify what works together and surface important configuration requirements or constraints. ### Alternatives & cross-reference Compare products across your portfolio or against competitive alternatives. ### Technical evidence Connect answers and recommendations back to the datasheets and documentation behind them. What can you do with Product Intelligence? ## Turn complex product questions into usable answers Product selection “I need a component that meets these environmental, performance, and interface requirements.” Identify the products that meet the requirements and explain why they fit. Application → Requirements → Specifications → Compatibility → Best-fit products → Evidence Cross-reference “What's our closest alternative to Competitor XYZ-400?” Identify the closest alternatives and show the technical evidence behind the comparison. Competitor product → Specifications → Performance → Applications → Your portfolio Technical answers “Which products support this configuration, and what documentation confirms it?” Give teams and customers answers without manually searching through product documentation. Question → Products → Technical documentation → Answer → Sources How is Product Intelligence different? ## Product Intelligence vs. PIM, search, and general-purpose AI PIM · Stores, organizes, and distributes product information. Enterprise search · Finds documents and information across systems. General-purpose AI · Generates and reasons from the information made available to it. Rapidflare Product Intelligence · Builds a structured understanding of products and the relationships between their specifications, applications, compatibility, alternatives, and technical evidence. PIM manages product information. Search finds it. Rapidflare understands it. Extraction accuracy, our benchmark - Rapidflare · · 95% - Contextual AI · · 62% - AWS Textract · · 49% [How we measured this](https://www.rapidflare.ai/methodology) How do teams use Product Intelligence? ## Put your Product Intelligence to work AI Agents ### Product intelligence for repeatable workflows Deploy specialized AI experiences built around specific product workflows. - [Product selection](https://www.rapidflare.ai/product/agents) - [Technical support](https://www.rapidflare.ai/product/agents) - [Competitive cross-reference](https://www.rapidflare.ai/product/agents) - [Sales enablement](https://www.rapidflare.ai/product/agents) - [Channel enablement](https://www.rapidflare.ai/product/agents) - [Proposal generation](https://www.rapidflare.ai/product/agents) [Explore AI Agents](https://www.rapidflare.ai/product/agents) Forge ### Product intelligence for complex, open-ended work Use your company's product intelligence inside a powerful AI environment for research, analysis, creation, and execution. - [Competitive research](https://www.rapidflare.ai/product/forge) - [Presentations](https://www.rapidflare.ai/product/forge) - [Training & enablement](https://www.rapidflare.ai/product/forge) - [Product analysis](https://www.rapidflare.ai/product/forge) - [Code & APIs](https://www.rapidflare.ai/product/forge) - [Multi-step workflows](https://www.rapidflare.ai/product/forge) [Explore Forge](https://www.rapidflare.ai/product/forge) How does Rapidflare Product Intelligence work? ## Connect → Understand → Activate 1 ### Connect your product knowledge Bring together catalogs, datasheets, product pages, technical documentation, and internal systems. 2 ### Build product understanding Rapidflare structures product information and maps relationships between products, specifications, applications, and sources. 3 ### Put it to work Use Product Intelligence through AI Agents, Forge, integrations, and customer-facing experiences. Product Intelligence built for complex technical industries ## Where Product Intelligence matters most ### Semiconductors & electronics Navigate large component catalogs, compare dense technical specifications, map applications to products, and help customers and sales teams identify the right parts. ### Physical security Understand products and compatibility across video surveillance, access control, cameras, VMS, and related security ecosystems. ### Distributors & channel organizations Make complex multi-vendor catalogs easier for internal sales teams, resellers, and customers to navigate and understand. Integrations ### Product Intelligence that fits your existing ecosystem Connect Rapidflare with the systems and sources where your product knowledge already lives. [Explore integrations →](https://www.rapidflare.ai/product/integrations) Deployment ### Built around your data and security requirements Deploy Rapidflare around your organization's infrastructure, governance, and security needs. [Explore deployment →](https://www.rapidflare.ai/product/deployment) FAQ ## Common questions about Product Intelligence What is a product intelligence platform? A product intelligence platform builds a structured understanding of a company's products: their specifications, relationships, applications, compatibility, alternatives, and the technical evidence behind them. A PIM stores and distributes product information and search finds it; a product intelligence platform understands it. Who uses Rapidflare Product Intelligence? Manufacturers and distributors with complex technical catalogs, and the sales, support, and channel teams who answer detailed product questions from that catalog every day. What information can Rapidflare use? Rapidflare builds its understanding from the sources your product knowledge already lives in: product catalogs, datasheets, BOMs, product pages, application notes, technical documentation, and internal systems. What can companies do with Product Intelligence? Turn complex product questions into usable answers: product selection, competitor cross-reference, technical support, sales and channel enablement, and proposal generation, delivered through AI Agents, Forge, integrations, and customer-facing experiences. Put your product knowledge to work ## Turn the product information your company already has into intelligence your teams, customers, and AI can use See how Rapidflare can turn your complex product portfolio into a trusted intelligence layer. [See Rapidflare in action](https://www.rapidflare.ai/contact) --- # Rapid Cross-Reference Agent Source: https://www.rapidflare.ai/product/rapid-cross-reference > Turn a competitor's part number into ranked matches from your own catalog, compared side by side, with the certification and pricing context behind the call. Rapid Cross-Reference Agent # Win the deal the moment a competitor's part number comes up Input a competitor's part number and get back the closest matches from your own catalog: ranked, compared side by side, and backed by the certifications and pricing context that explain why yours is the better choice. Built for the moment a prospect says “we're using Product X from Competitor Y,” so your team never has to answer that with “let me get back to you.” [See Cross-Reference in action](https://www.rapidflare.ai/contact) - Natural-language competitor lookup - Side-by-side comparisons - Win-ready battlecards - Live in production Where competitive deals stall ## Every vendor names the same spec differently GHz vs. MHz. Field-of-view vs. lens description. Voltage ranges. Power ratings. Manual part-to-part matching across catalogs is slow, error-prone, and easy to get wrong under deal pressure. Today, answering “what's your equivalent to Competitor Part X?” usually means: Hand-built cross-reference spreadsheets · One-by-one manufacturer site lookups · Legacy spec databases · Physical catalogs · Google, more often than anyone would admit Rapid Cross-Reference turns that into a single query, with the comparison and the reasoning behind it. What is Rapid Cross-Reference? ## A competitor part number in, a ranked and justified match out A user inputs a competitor's part number or device spec. Rapid Cross-Reference normalizes that spec across vendor vocabularies, runs a deep comparison against your catalog, and returns the closest matches, with a side-by-side comparison that explains why your product is the better choice, including certifications and pricing context to justify any price difference. Competitor part · → · Normalize · → · Compare · → · Rank · → · Justify Why this is its own agent ## The “making sense selling” methodology Cross-reference could live inside a chat interface. But the backend work required to normalize data and compare specifications across multiple competitors, reliably and at catalog scale, is significant enough to justify treating it as a dedicated Agent. Its value isn't just finding a similar part. It's making the case for why yours is the right one. Side-by-side feature comparison, not just a part number match Certifications and compliance context included automatically Pricing context that justifies the difference, rather than hiding from it Built for both marketing content and live sales conversations How Rapid Cross-Reference works ## From a competitor's part number to a comparison you can send 1 ### Input a competitor part A rep, marketer, or self-service visitor enters a competitor's part number or a plain-language spec description. No need to already know your catalog's naming. 2 ### Normalize across vendor vocabularies Unit conversions and naming-convention differences are resolved automatically: GHz vs. MHz, field-of-view vs. lens description, voltage ranges, power ratings, interface protocols, and similar mismatches. 3 ### Run a deep spec comparison Rapid Cross-Reference compares form factor, electrical characteristics, operating conditions, and functional equivalence, not just keyword overlap. 4 ### Return a ranked shortlist The 3 to 5 most similar parts from your own catalog, ranked by a compatibility score, showing which specs match, which differ, and the trade-offs. 5 ### Make the case A side-by-side comparison table (features, certifications, and pricing) makes the reasoning explicit, including why your product is the better choice and how to justify any price gap. Advanced · Taoglas For deployments that need more than a real-time lookup, an advanced variant runs on Rapidflare's long-running agent harness to perform competitive pricing benchmarking, flagging over- and under-priced SKUs, and product-gap analysis, surfacing where a competitor has something you don't yet have a close match for. What changes ## From hours of manual comparison to an answer in the conversation Hours comparing datasheets · → · Seconds Miss compatible parts due to terminology differences · → · Intelligent parameter normalization Limited to your own vendor knowledge · → · Works across unlimited catalogs Static comparison spreadsheets · → · Real-time catalog updates Requires engineering expertise · → · Self-service for sales and procurement What it can do ## Built for catalog-scale competitive matching ### Multi-vendor catalog integration Connect multiple supplier catalogs and product databases, with naming conventions, units, and spec formats normalized automatically. ### Smart parameter normalization Handles GHz vs. MHz, FOV vs. lens description, voltage ranges, power ratings, interface protocols, and similar mismatches across vendors. ### Precision cross-referencing Input any part, instantly get the 3 to 5 most similar parts from an alternate vendor catalog, ranked by compatibility score. ### Deep spec analysis Compares technical specs, form factors, electrical characteristics, operating conditions, and functional equivalence, not just keywords. ### Compatibility scoring Shows which specs match, which differ, and the trade-offs, instead of a flat yes/no equivalence. ### Vendor-agnostic intelligence Works across semiconductors, sensors, cameras, modules, connectors, power supplies, and more. ### Auto-updated competitor data Continuously monitors competitor websites, product pages, and public announcements. ### Smart migration guidance The moment a prospect says "we're using Product X from Competitor Y," the Agent identifies the equivalent and the migration path. ### Natural language queries Ask directly, "How does our solution compare to \[Competitor\]?", without needing to know a part number at all. ~24% On some of our hubs, competitor cross-reference queries account for nearly a quarter of all traffic. This isn't a nice-to-have feature, it's one of the most-used capabilities in production. Who's using it ## From large-catalog distributors to specialized manufacturers Taoglas ### Antenna manufacturer Our most developed cross-reference deployment: SKU matching against five named competitors, competitor pricing benchmarking, and a leadership-facing competitive-analysis variant built on Rapidflare's long-running agent harness. Alibi Security ### Physical security Cross-reference is a real, shipped capability inside Alibi's AskAlibi support Agent, helping resellers match competitor products to the closest Alibi equivalent. Illustrative examples of the catalog sizes and use cases Rapid Cross-Reference is built for: ~35K SKUs ### Large-catalog distributor Cross-reference as the top-priority use case in active evaluation, the scale where manual matching breaks down entirely. End-of-life replacement ### Power component manufacturer Matching against multiple named competitors for like-for-like replacement when a part is discontinued. Multi-vendor catalog ### Electronic components distributor Thousands of SKUs across dozens of brands, the classic case for automated, vendor-agnostic cross-referencing. Trust, not just speed ## When it can't verify a match, it says so A plausible-looking match that quietly ignores a real spec gap is worse than no match at all. Rapid Cross-Reference is built to flag what it can't confirm rather than guess, showing where a candidate falls short instead of presenting it as an equivalent. Under the hood ## Built on the right engine for the job Blaze ### Real-time lookups Standard cross-reference queries run on Rapidflare's production harness, built for instant, conversational answers. Forge ### Long-running competitive research A single competitive engagement can touch hundreds of part numbers and span weeks. Advanced pricing and gap analysis run on Rapidflare's long-running agent harness built for exactly that. Every match includes full explainability with citations, powered by purpose-built technical-PDF extraction and a knowledge graph that turns atomic product facts into semantic relationships, enabling precise queries, comparisons, and cross-references. FAQ ## Frequently asked questions What is Rapid Cross-Reference? Rapid Cross-Reference is an AI Agent that takes a competitor's part number or spec and returns the closest matching products from your own catalog, ranked by compatibility, with a side-by-side comparison and pricing context. How does it handle different vendors describing specs differently? Rapid Cross-Reference normalizes specifications across vendor vocabularies (unit conversions, naming-convention differences, and format mismatches) before comparing them, so a GHz-vs-MHz or FOV-vs-lens-description mismatch doesn't cause a missed match. Is this built for sales or for procurement and engineering? Both. It's most commonly used by sales and marketing teams to respond to competitive situations, but the same underlying matching and normalization also supports procurement and engineering teams doing part replacement or migration research. What happens if there's no good equivalent in our catalog? Rapid Cross-Reference is designed to say so rather than force a weak match. It can show the closest available options along with where they fall short, instead of presenting an unqualified part as equivalent. Can it also do competitive pricing analysis? For select deployments, yes. An advanced variant can run competitive pricing benchmarking and product-gap analysis across a competitor's catalog. Talk to us about whether that fits your use case. Is Rapid Cross-Reference a standalone product or a feature of another Agent? It can run as its own experience or as a capability inside another Rapidflare Agent, such as Technical Support. The right fit depends on how your team wants to use it. What catalogs does it work across? Rapid Cross-Reference is vendor-agnostic and works across categories including semiconductors, sensors, cameras, modules, connectors, power supplies, and other technical component catalogs. Never lose a deal to “let me check on that” ## Turn a competitor's part number into your best argument for why you win Ranked matches, side-by-side comparisons, and the pricing context to back them up. [See Rapid Cross-Reference in action](https://www.rapidflare.ai/contact) --- # Rapid Product Selection Agent Source: https://www.rapidflare.ai/product/rapid-product-selection > AI-guided product discovery for complex technical catalogs. Turn plain-language requirements into specific, explainable, source-backed product recommendations. Where product selection usually goes wrong ## Product selection should start with the application, not the filter A traditional product selector starts by asking the buyer to choose specifications. That works when the buyer already knows exactly what they need. Often, they don't. They start with: Rapidflare starts there. The buyer describes the problem. Rapidflare figures out which product requirements matter. What is a Product Selection Agent? ## AI-guided product discovery for complex technical catalogs A Product Selection Agent is an AI-guided product discovery system that helps buyers find the right product from a complex technical catalog using natural language. Instead of requiring someone to translate their application into a complete set of filters, Rapidflare interprets the requirement, identifies the technical dimensions that matter, asks targeted follow-up questions, and narrows the catalog toward the products that best fit. It combines the accessibility of a conversation with the rigor of structured technical product selection. From a vague requirement to the right product ## Rapidflare behaves more like an applications engineer than a search bar Structured product reasoning, not just document search ## Your catalog becomes something AI can reason over Rapid Product Selection Agent isn't simply a chatbot searching a collection of PDFs. Rapidflare builds Product Intelligence across the catalog, combining structured product information with the technical documentation behind it. That means Rapidflare can reason over: ### Products Individual SKUs and product families. ### Typed specifications Frequency, interfaces, memory, temperature, connectors, dimensions, and other category-specific attributes. ### Product relationships Families, generations, accessories, compatible components, and alternatives. ### Applications The requirements and use cases each product is designed to support. ### Technical documentation Datasheets, application notes, product pages, and other supporting sources. The result is closer to a technical product decision system with a conversational interface than a search-and-summarize chatbot. Explainable product recommendations ## Every recommendation should come with receipts Technical product selection is too important for “this looks like the best option.” Rapidflare shows how the recommendation was reached. The buyer sees both the strongest match **and the products that were ruled out**. Supporting claims remain connected to their technical sources, so users can inspect the evidence behind the answer. Sometimes the right answer is no product ## A trustworthy selector has to be willing to come up empty If no product satisfies the buyer's hard requirements, Rapidflare doesn't need to force a recommendation. No product currently meets every requirement. Product selection that follows your business rules ## Your best sales-engineering judgment becomes part of the experience Technical specifications aren't the only thing that determines a good recommendation. Your team already has rules about how products should be selected and positioned. For example: It knows when to guide, and when to get out of the way ## Not every buyer needs an interview Product Selection Agent vs. traditional product discovery ## Different ways to answer “Which product is right for me?” One experience for external buyers and internal teams ## Put your product expertise wherever the selection decision happens Built for complex technical catalogs ## Where Product Selection matters most ### Semiconductors & electronic components Guide buyers from application requirements to the right chip, module, component, or product family across dense technical specifications. ### Antennas & connectivity Translate use cases into frequency, gain, connector, mounting, environmental, and form-factor requirements. ### Embedded & industrial computing Help engineers navigate processor families, memory, interfaces, operating environments, form factors, and product generations. ### Physical security Guide customers toward appropriate cameras, access-control hardware, surveillance products, and compatible system components. ### Industrial & technical equipment Turn application requirements into recommendations without requiring buyers to master the catalog before they start. FAQ ## Frequently asked questions What is a Product Selection Agent? A Product Selection Agent is an AI-guided system that helps buyers find the right product from a complex catalog by describing their requirements in natural language. Rapidflare translates application-level requirements into technical constraints, evaluates the relevant products, asks clarifying questions when necessary, and returns explainable recommendations grounded in product data and technical documentation. How is a Product Selection Agent different from parametric search? Parametric search requires the buyer to know which product attributes matter and what values to filter for. A Product Selection Agent allows the buyer to start with the problem they are trying to solve. It identifies the technical requirements that matter, asks for missing information, and evaluates the catalog on the buyer's behalf. How is Rapidflare different from a chatbot over product documentation? Rapidflare combines conversational interaction with structured Product Intelligence about products, specifications, relationships, applications, and technical sources. The Agent can therefore evaluate products against requirements and explain why products meet or fail those requirements rather than simply retrieving related passages from documents. Can the Product Selection Agent ask follow-up questions? Yes. When a requirement is too broad to make a reliable recommendation, Rapidflare can ask targeted follow-up questions to narrow the decision. It retains conversational context, so recommendations can be updated as requirements change. What happens if no product meets the requirements? Rapidflare can explicitly return no qualifying product rather than forcing a near-match. It can explain which requirements were met, which were not, and which products came closest. Can our company define product-selection rules? Yes. Product-selection behavior can be configured around company-specific rules such as product lifecycle status, preferred product generations, selection priorities, trade-off guidance, and escalation requirements. Is the Product Selection Agent only customer-facing? No. The same capability can support external buyers as well as internal sales teams, field application engineers, distributors, and channel partners. Turn “what should I use?” into an answer your buyers can trust ## Give customers and teams a faster way to move from application requirements to the right product With the reasoning and technical evidence behind every recommendation. [See Rapid Product Selection Agent in action](https://www.rapidflare.ai/contact) --- # Rapid Proposals Agent Source: https://www.rapidflare.ai/product/rapid-proposals > An AI agent that turns RFQs and RFPs into fast, accurate, compliance-checked responses grounded in your specifications, approved content, and prior proposals. Rapid Proposals Agent # Turn incoming RFQs into faster, more accurate proposals Bring together product specifications, approved technical content, previous responses, and supporting documentation to help your team prepare proposals and RFP responses faster, without sacrificing accuracy on the details that win or lose the deal. Incoming RFQs rarely arrive clean. Rapid Proposals works through the ambiguity: missing part numbers, legacy customer codes, compliance requirements buried in the notes. Your best responses stop depending on which rep happens to pick it up. [See Rapid Proposals in action](https://www.rapidflare.ai/contact) - RFP & RFQ response - Compliance validation - Source-backed proposals - Live with sales & proposal teams Where proposals slow down ## Your best response shouldn't depend on which rep opens the RFQ first A real RFQ package might include: A mixed .zip of 50+ files · Legacy internal part codes · Compliance requirements buried in notes · A response window measured in weeks Response quality ends up depending heavily on which rep works it: tribal knowledge that doesn't scale, and walks out the door when experienced people leave. Rapid Proposals turns that tribal knowledge into something the whole team can use, on every RFQ, not just the ones your best rep happens to see. What is Rapid Proposals? ## An AI Agent that turns an incoming RFQ into a response you can stand behind Rapid Proposals ingests an incoming RFQ or RFP, works through it line by line, cross-references your product specifications, pricing, and prior approved content, and drafts a response grounded in your own technical documentation, with every claim traceable back to a source. RFQ intake · → · Cross-reference · → · Draft response · → · Compliance check · → · Submit How Rapid Proposals works ## From a messy RFQ folder to a response your team can stand behind 1 ### Ingest the RFQ package Real RFQ packages arrive as a mixed set of PDFs, spreadsheets, and Word documents, sometimes 50 or more files in one folder. Rapid Proposals reads the whole package and produces a structured summary: what's inside, what it means, and what's due when. That summary includes each file's name and location, a short description, the owning department, key content, why it matters, and the due date. 2 ### Work through it line by line Rapid Proposals cross-references inventory and pricing across your internal systems for each line item, and flags the lines that need a human's judgment call, surfacing the specific clarifying question a rep should ask rather than guessing. 3 ### Check the response against every requirement Rapid Proposals can produce an automated compliance-validation report, mapping each RFP requirement line by line to the relevant technical response content and marking it Pass, Gap, or Fail, so nothing gets missed before it goes out the door. On a recent enterprise deal of our own, the output was three parts: a narrative response addressing each RFP section, a compliance matrix mapping every requirement to a compliance statement, and supporting materials including the SOC 2 report, API docs, and case studies. 4 ### Draft the response in your format Rapid Proposals can produce a structured proposal outline and a full structured response, with parameters for labor rate, currency, geography, locale, and language. Rolling Wireless For Rolling Wireless, that means taking a structured RFQ spec, like a technical requirements spreadsheet, and drafting responses directly inside a dedicated RFQ workspace. The scale this needs to hold up at ## Complex products mean high-stakes, time-boxed proposals A physical security integrator running Rapid Proposals handles roughly **750 proposals a year** on a **four-week response window**. Weeks → Minutes · Typical proposal turnaround 1 day · Sales ramp-up to competency, vs. weeks 30% · Reduction in L1 support call volume Why not just use a generic AI assistant? ## Generic AI knows how to answer; Rapidflare knows your products > “ChatGPT, Claude, and Gemini are good at reasoning. What none of them know out of the box is your catalog, your compliance requirements, or which of your parts work together. We ground that same intelligence in your technical documentation, so the answer it gives is accurate to your specific products.” The most common comparison we hear is Microsoft Copilot. Copilot does generic retrieval across your files. Rapid Proposals goes further, into the execution flow itself, with product intelligence behind every answer. What teams are saying ## Live with sales and proposal teams today Rapid Proposals is live and deployed with proposal and sales teams at organizations including **Rolling Wireless**, each running it against their own RFQ workflows and technical content. The other side of the same RFQ ## This is the sell-side, and there's a buy-side version too Rapid Product Selection Agent helps buyers on your own site move from a vague requirement (no SKU, no brand, just an application) to a submitted, qualified RFQ. It's live in production today via a McFadyen Digital deployment. [Explore Rapid Product Selection →](https://www.rapidflare.ai/product/rapid-product-selection) Where it fits in your stack ## Connects to the systems your proposals already depend on PIM · ERP · E-commerce catalog · CRM · CPQ / quoting tools · Technical documentation · SharePoint · Salesforce · Google Drive · Jira & Confluence · NetSuite Deployable across web, Slack, mobile, CRM, email, and partner portal. [See all 950+ integrations →](https://www.rapidflare.ai/product/integrations) Built around your process ## Your business rules, not a generic template Every response can reflect the way your organization sells: reusable approved answers, consistent pricing logic, and the compliance bar your best reps already hold themselves to. Your catalog and content provide the facts. · Your team's judgment sets the bar. · Rapid Proposals applies it on every RFQ, not just the ones your best rep happens to see. FAQ ## Frequently asked questions What is Rapid Proposals? Rapid Proposals is an AI Agent that ingests incoming RFQs and RFPs and helps sales and proposal teams respond accurately and quickly, grounded in your product specifications, approved technical content, prior responses, and supporting documentation. Can it handle a messy RFQ package with dozens of files? Yes. Rapid Proposals can ingest a full RFQ package (a mixed set of PDFs, spreadsheets, and Word documents) and produce a structured summary of what's inside before working through the response. Does it check our response against the RFP's requirements? Yes. Rapid Proposals can produce a requirement-to-response compliance matrix that maps each RFP requirement line by line to the relevant response content and marks it Pass, Gap, or Fail. Does Rapid Proposals replace our proposal team? No. It's designed to handle the systematic, time-intensive parts of a response (intake, cross-referencing, compliance checking, first-draft language) and flag the lines that need human judgment, so your team spends more time on strategy and less on assembly. Can it connect to our CPQ and quoting systems? Yes. Rapid Proposals is designed to integrate with CPQ and quoting tools, CRM, ERP, PIM, and technical documentation systems so a response can flow directly into your existing workflow. What AI models power Rapid Proposals? Rapidflare uses a domain-aware AI pipeline built specifically around product and technical knowledge, rather than a single off-the-shelf model. The focus is on grounding responses in your own product data and documentation. Is there a buy-side version of this? Yes. Rapid Product Selection Agent helps buyers on your own site move from a vague requirement to a submitted, qualified RFQ. Rapid Proposals then helps your team respond to that RFQ, and to RFQs arriving through any channel. Stop letting the RFQ pick the winner ## Give every rep the same accurate, compliance-checked response, in minutes, not weeks Grounded in your product specifications, approved content, and prior proposals. [See Rapid Proposals in action](https://www.rapidflare.ai/contact) --- # Rapid Technical Support Agent Source: https://www.rapidflare.ai/product/rapid-technical-support > Technical support that handles the hard questions: source-backed answers grounded in your datasheets, firmware, logs, and engineering docs. Rapid Technical Support Agent # Technical support that can handle the hard questions Give customers, partners, and support engineers fast access to the technical knowledge behind your products, from datasheets and installation guides to firmware procedures, engineering notes, logs, and resolved support issues. Rapidflare searches across fragmented technical knowledge, reasons across multiple sources, and returns precise, source-backed answers without forcing someone to know where the answer lives. [See Technical Support in action](https://www.rapidflare.ai/contact) - Technical Q&A - Multi-source reasoning - Source-backed answers - Engineering support Where technical knowledge gets lost ## Your engineers should solve problems, not search for answers Technical product knowledge rarely lives in one place. The answer might be buried in: A datasheet · An installation drawing · A firmware guide · An application note · An internal wiki · A Jira ticket · A resolved support case · A release note · An engineering diagram · A code repository For a customer, finding that information can mean opening dozens of documents. For a support engineer, it means spending valuable time searching instead of solving the problem. Rapidflare turns that fragmented technical knowledge into one place to ask the question. What is a Technical Support Agent? ## AI-guided answers, grounded in your trusted technical knowledge A Technical Support Agent is an AI system designed to answer specific product, integration, configuration, and troubleshooting questions using a company's trusted technical knowledge. Unlike a Product Selection Agent, which guides a buyer toward the right product, the Technical Support Agent starts with a technical question and works toward the most complete, accurate answer. Question · → · Retrieve · → · Reason · → · Answer · → · Evidence Rapidflare can search iteratively across multiple technical sources, combine the relevant information, and return a single answer with the supporting documentation attached. From documentation lookup to engineering support ## Handle the full range of technical questions Not every support question has the same level of complexity. Rapidflare can help with straightforward product questions as well as deeper engineering workflows. Find a technical specification “Does this antenna cover Band 72?” Return the direct answer, the relevant frequency range, and the exact supporting source. Find a drawing or installation guide “Can you pull the footprint drawing for this part?” Surface the relevant technical diagram or document without requiring the user to hunt through a document library. Explain installation requirements “What's the keep-out area for this antenna?” Bring together the relevant specifications, drawings, and installation guidance into one answer. Walk through a procedure “What is the exact command sequence to enable secure boot on this module family?” Return the documented sequence with the relevant steps and sources. Troubleshoot a technical issue “What logs should I collect to debug this timeout?” Reason across support documentation and engineering knowledge to explain what information is required and how to collect it. Analyze technical context “Paste an error message, bug reference, configuration, or technical log into the conversation.” Rapidflare can use that context alongside your technical knowledge to help support teams investigate the issue. More than a one-shot document search ## Complex questions rarely live in one document A traditional search system retrieves the document most similar to the query. But real technical support questions often span multiple sources. A question about an integration issue might require: Product documentation · + · Firmware behavior · + · Configuration guidance · + · Resolved engineering issue One coherent, synthesized answer The goal isn't to find the best document. · The goal is to resolve the question. Rapidflare's existing support deployments are designed around unified technical knowledge spanning sources such as SDK documentation, GitHub, developer portals, Jira, Confluence, and other internal repositories. Every technical answer should show its work ## Source-backed answers, down to the supporting evidence For technical support, “the AI said so” isn't good enough. Rapidflare keeps factual answers connected to the documentation behind them. A response can include: The answer · Relevant specifications · Step-by-step procedures · Technical diagrams · Tables · Supporting documents · Citations to the relevant source · The specific passage supporting the claim So engineers can verify the answer instead of choosing between trusting the AI and repeating the research themselves. Answer quickly. Verify immediately. Keep the conversation, not just the query ## Technical troubleshooting happens across multiple turns Real support conversations rarely fit inside a single perfectly formed question. A user might ask: “How do I capture a RAM dump while the module is in standby?” “Does USB need to remain connected? I thought standby meant disconnecting it.” Rapidflare keeps the technical context from the conversation and addresses the apparent contradiction instead of treating the follow-up as a completely new search. That matters when troubleshooting involves: Previous steps · Device state · Configuration · Error messages · Firmware versions · Logs · Follow-up observations The conversation becomes part of the troubleshooting context. When the documentation doesn't say, Rapidflare shouldn't guess ## Technical trust starts with knowing the limits If a specification, procedure, or product behavior isn't supported by the available technical knowledge, Rapidflare can say so. It doesn't need to fill the gap with a plausible-sounding answer. Instead, it can: - Identify what is documented - Explain what cannot be verified - Point to the relevant source - Ask for additional context - Escalate the question when human expertise is required The same applies when a question falls outside the Agent's intended scope. A useful technical support system knows when to answer, and when not to. Built around your support rules ## Your escalation logic becomes part of the Agent Different support organizations have different boundaries. Rapidflare can be configured around rules such as: Redirect pricing and quote questions to sales Escalate stock or lead-time questions Never expose restricted internal documentation Use internal sources to reason without exposing them externally Prefer specific drawings or figures when available Require documentation before asserting a specification Route unsupported questions to the right person Apply customer- or partner-specific access rules That means the Agent isn't simply connected to your documentation. · It behaves according to the way your support organization operates. One support layer. Different audiences. ## Deploy technical intelligence where each user needs it ### Customer self-service Give customers immediate answers to product, installation, integration, certification, and troubleshooting questions. Reduce repetitive support requests without forcing customers to search through technical portals themselves. ### Partner and developer support Give OEMs, integrators, developers, distributors, and technical partners access to the documentation and guidance relevant to their products and configurations. Rapidflare can support dedicated experiences scoped to specific customers or partner groups. ### Internal support engineers Give support teams access to deeper internal knowledge, resolved issues, engineering notes, and escalation guidance. Help engineers find the context behind difficult questions without searching manually across repositories. ### Escalation teams Use Rapidflare as an internal technical intelligence layer for the questions that require deeper investigation. Bring proprietary knowledge and prior support history into the workflow while keeping access restricted to the appropriate users. Rolling Wireless, for example, uses distinct Rapidflare support experiences for OEM partners, V2X customers, and internal escalation engineers. Product Selection vs. Technical Support ## Same Product Intelligence, different job Product Selection Agent Question “What should I use?” Optimized for Pre-sale product discovery Behavior Understands an application, asks clarifying questions, narrows the catalog, and recommends the best-fit product. Application → Constraints → Candidates → Recommendation [Explore Product Selection →](https://www.rapidflare.ai/product/rapid-product-selection) Technical Support Agent Question “How does this work?” or “Why isn't this working?” Optimized for Technical support and integration Behavior Searches technical knowledge, reasons across relevant sources, and returns a precise, referenced answer. Question → Evidence → Reasoning → Answer Product Selection helps someone choose the right product. Technical Support helps them successfully use it. · Both are powered by the same Rapidflare Product Intelligence layer. How does Rapidflare Technical Support work? ## From a scattered question to one referenced answer 1 ### Connect the technical knowledge behind your products Bring together sources such as: Datasheets · Manuals · Application notes · Installation guides · SDK documentation · Product portals · Internal knowledge bases · Jira and Confluence · Support history · Engineering documentation · Code repositories 2 ### Ask the technical question Users can ask questions naturally without needing to know which document, repository, or team owns the answer. They can also provide additional context such as: Product numbers · Error messages · Logs · Bug references · Configuration details · Firmware versions 3 ### Rapidflare retrieves and reasons across the relevant sources The Agent can search iteratively rather than relying on a single retrieval result. When the answer requires information from multiple sources, Rapidflare combines that evidence into one response. 4 ### Get a source-backed answer The user gets the answer in the format best suited to the question: Direct response · Comparison table · Step-by-step procedure · Troubleshooting checklist · Technical diagram · Source citations · Escalation guidance Technical support where engineers already work ## Support that appears in the flow of work, not another destination Technical knowledge is more useful when it appears in the workflow rather than requiring another destination. Rapidflare support experiences can be deployed through customer-facing and internal channels, including web experiences and developer communities. Rapidflare already supports production use in developer environments where engineers receive source-backed technical answers in the flow of their work. Built for complex technical products ## Where Technical Support matters most ### Semiconductors Support questions spanning device architecture, SDKs, firmware, hardware revisions, configuration, and integration. ### Automotive & IoT Help engineering teams navigate connectivity modules, software-defined hardware, certifications, firmware, and complex system dependencies. ### Electronic components Answer questions about specifications, installation, mechanical drawings, compatibility, environmental requirements, and integration. ### Physical security Support customers across cameras, access control, VMS, integrations, configuration, and system compatibility. ### Developer ecosystems Give developers immediate access to SDK documentation, technical references, integration examples, resolved issues, and engineering knowledge. FAQ ## Frequently asked questions What is an AI Technical Support Agent? An AI Technical Support Agent answers product, integration, configuration, and troubleshooting questions using a company's trusted technical knowledge. Rapidflare retrieves and reasons across relevant technical sources to provide answers with supporting evidence. How is an AI Technical Support Agent different from enterprise search? Enterprise search primarily helps users find documents. Rapidflare is designed to answer the technical question itself by retrieving relevant information across one or more sources, reasoning over that information, and returning a source-backed response. Can Rapidflare answer questions across multiple documents? Yes. Technical questions often require information from multiple sources. Rapidflare can retrieve information iteratively across available technical knowledge and combine the relevant evidence into one answer. Can users paste logs or error messages into the Agent? Users can provide technical context such as logs, error messages, bug references, configuration information, and other troubleshooting details as part of the conversation. Rapidflare can use that context alongside the connected technical knowledge when generating the response. What happens if Rapidflare can't verify the answer? Rapidflare can explicitly state when the available sources don't contain enough information to support an answer rather than guessing. The Agent can then ask for more information or route the user toward the appropriate support path. Can different users have access to different technical knowledge? Rapidflare can support different experiences for customers, partners, and internal teams so that the knowledge available to each Agent reflects the intended audience and access requirements. Does Rapidflare replace technical support engineers? No. Rapidflare is designed to handle repetitive information retrieval, routine technical questions, and knowledge-intensive research so technical experts can spend more time on issues that require engineering judgment. Turn fragmented technical knowledge into answers you can trust ## Give support teams, partners, and customers one place to ask complex product questions And get precise answers with the technical evidence behind them. [See Rapid Technical Support in action](https://www.rapidflare.ai/contact) --- # Security Source: https://www.rapidflare.ai/product/security > SOC 2 Type II, tenant isolation, no shared training, and how access to Rapidflare works: sign-in, the public-site agent, and ingestion. Security # Enterprise-grade by construction Security is not a bolt-on. The same controls that make the answers trustworthy make the platform safe to hold your proprietary knowledge. [![AICPA SOC 2 Type II](https://www.rapidflare.ai/badges/aicpa-soc.png)SOC 2 Type II](https://app.vanta.com/rapidflare.ai/trust/pu8d0fi1rb1eqr6m30zh3h) [Visit the Trust Center](https://app.vanta.com/rapidflare.ai/trust/pu8d0fi1rb1eqr6m30zh3h) [Read the privacy policy](https://www.rapidflare.ai/privacy) The controls ## What is audited, isolated, and never shared SOC 2 Type II ### Independently audited, continuously monitored Our security controls are audited by an independent firm and monitored continuously. The report is available to customers and serious evaluators under NDA through the Trust Center. Tenant isolation ### Your data is yours, and stays in your tenant Documentation and product data live in an isolated tenant, encrypted in transit and at rest. Nothing is pooled with another customer. No shared training ### Your content never trains a model anyone else touches Customer content is used to answer your users, not to train shared foundation models. Cited by default ### Every answer links back to its source Inline citations point at the document and page each claim came from, so any answer can be verified before it is acted on. Scoped and controlled ### The agent says only what you allow Knowledge hubs are permissioned, answers are scoped to the sources you connect, and evaluation suites run on your documents before go-live and after every change. How access works ## Four doors, each with its own lock The detailed guides live on the docs site; this is the shape of it. ### Signing in to the dashboard and agents Google and Microsoft sign-in, email and password, or single sign-on through your identity provider on the enterprise plan. Admin and member roles keep conversation access where it belongs. [Login and SSO guide →](https://docs.rapidflare.ai/security/auth) ### The agent on your public site Publishable API keys are bound to the domains you allow. Every request is attested with AppCheck and scored by invisible reCAPTCHA, so a cloned page or a bot cannot use your key. [Widget security guide →](https://docs.rapidflare.ai/security/widget) ### Reading your documentation Ingestion reaches your systems from four static IP addresses you can allowlist, authenticates with the credentials you configure, and signs every crawl request so you can verify it is us. [Ingestion IPs and crawler verification →](https://docs.rapidflare.ai/security/network) ### What we collect about people Names, work emails, and contact or billing details you give us, plus standard technical logs. No sensitive personal information. Conversation content is processed to answer and improve, and retained per your contract. [Data privacy summary →](https://docs.rapidflare.ai/security/data-privacy) ## Want the SOC 2 report or a security review? [Talk to the team](https://www.rapidflare.ai/contact) --- # Website agent Source: https://www.rapidflare.ai/product/website-agent > Turn your catalog and docs into an agent on your site that answers technical questions instantly, grounded in your data. Product · Website agent # Turn your catalog and docs into an agent on your site Your buyers ask hard technical questions on your website. Rapidflare answers them in seconds, grounded in your own datasheets, with a source on every line. [Book a demo](https://www.rapidflare.ai/contact) [Ask the agent](https://www.rapidflare.ai/contact) Trusted by the companies your customers already buy from ![AMD](https://www.rapidflare.ai/logos/amd.png)![Taoglas](https://www.rapidflare.ai/logos/taoglas.png)![Qorvo](https://www.rapidflare.ai/logos/qorvo.png)![Amphenol](https://www.rapidflare.ai/logos/amphenol.png)![Brivo](https://www.rapidflare.ai/logos/brivo.png)![Eagle Eye](https://www.rapidflare.ai/logos/eagle-eye.png)![Macnica](https://www.rapidflare.ai/logos/macnica.png)![Swift Sensors](https://www.rapidflare.ai/logos/swift-sensors.png)![Portal](https://www.rapidflare.ai/logos/portal.png)![Critical Link](https://www.rapidflare.ai/logos/critical-link.png)![Sage](https://www.rapidflare.ai/logos/sage.png)![Alibi Security](https://www.rapidflare.ai/logos/alibi.png)![Tolomatic](https://www.rapidflare.ai/logos/tolomatic.png)![Actuate](https://www.rapidflare.ai/logos/actuate.png)![DeepX](https://www.rapidflare.ai/logos/deepx.svg)![McFadyen Digital](https://www.rapidflare.ai/logos/mcfadyen.png)![Rolling Wireless](https://www.rapidflare.ai/logos/rolling-wireless.png)![Security Industry Association](https://www.rapidflare.ai/logos/sia.png) How it works ## From your documentation to accurate answers, in one deploy 1. 01 ### Connect your sources Point Rapidflare at your catalogs, datasheets, install guides, and internal docs. No re-tagging, no clean-up first. 2. 02 ### Customize the agent Set its voice, its scope, and the tasks it handles, from a support answer to a full proposal. Our engineers stand it up. 3. 03 ### Deploy on your site Embed it as a widget or a full page. It goes live where your buyers already are, grounded in your data. Capabilities ## Built to run in front of your customers, every day - ### Grounded, cited answers Every answer traces back to the source, inline. No invented specs, no confident guesses. - ### Reads the hard documents Tables, drawings, and firmware revisions, not just prose. 95% extraction accuracy on our held-out set. [How we measured this](https://www.rapidflare.ai/methodology) - ### Beyond a chatbot Selection, cross-reference, and quote-ready proposals, not only question and answer. A fleet, not a feature. - ### Full visibility See every question your buyers ask, and find the gaps in your documentation before they cost you a deal. > Without Rapidflare, we would have lost our biggest customer. They made it easy for our integrators to find information about our complex products. Why it is accurate ## A chatbot pointed at a folder will guess; this will not Accuracy is the objection that kills an AI deal in this industry, so we measured it and published how. Extraction accuracy, our benchmark - Rapidflare · · 95% - Contextual AI · · 62% - AWS Textract · · 49% [How we measured this](https://www.rapidflare.ai/methodology) ## See it run on your own catalog [Book a demo](https://www.rapidflare.ai/contact) - **Free to test**Try it on your own catalog before you commit. - **Live in days**Forward-deployed engineers stand it up, white-glove. - **SOC 2 Type II**Your data stays yours, never used to train shared models. FAQ ## The questions you are about to ask What is the website agent? An AI agent that lives on your site and answers technical questions about your products, grounded in your own documentation, with a source on every line. How accurate is it, and does it hallucinate? It reads your documents at 95% extraction accuracy and cites the source for every answer. When it does not know, it says so instead of guessing. Is my data secure? Yes. Rapidflare is SOC 2 Type II. Your documentation grounds the agent and is never used to train shared models. How much work is the setup? Very little on your side. Our forward-deployed engineers connect your sources and stand the agent up. Most customers are live within days. What sources can it use? Catalogs, datasheets, install guides, knowledge bases, and internal docs. It pulls them into one graph so answers are precise and relational. Can I brand it and place it where I want? Yes. Style it to match your site and deploy it as a widget or a full page, and on other surfaces like Slack, CRM, and email. --- # By Industry Source: https://www.rapidflare.ai/by-industry > Rapidflare for manufacturers, OEMs, distributors, integrators, semiconductor, physical security, industrial automation, sensors, RF and B2B e-commerce. # Industries where technical sales runs through an engineer Thousands of SKUs. Datasheets that run to thousands of pages. Configurable parts with no fixed part number. A customer who describes a job or a requirement, not a product they already have in mind. Rapidflare connects your disparate knowledge sources into a structured catalog and a detailed knowledge graph, then builds AI agents that select the right part, answer the technical question, write the proposal, or automate any other step of the sales process. [Book a demo](https://www.rapidflare.ai/contact) [See it by team](https://www.rapidflare.ai/by-team) 10 industries ## Multiple industries, the same problem Every one of them is missing a product intelligence layer, so the right information never reaches the right person. That routes technical questions through your sales engineers instead of your product, and it slows the sales cycle, shrinks deal size and stalls deal velocity. Pick your industry to see how Rapidflare fixes it. [Manufacturers ### Automate the long-tail of customers Your parametric search works when the customer already knows the parameters. Your best application engineers work when they have time for the account. Rapidflare answers "I’m designing an automotive infotainment system, what should I use?" the way your best AE would, for every customer, including the long-tail who never got that engineer’s attention at all. ![AMD](https://www.rapidflare.ai/logos/amd.png)![Qorvo](https://www.rapidflare.ai/logos/qorvo.png)![Taoglas](https://www.rapidflare.ai/logos/taoglas.png)![Critical Link](https://www.rapidflare.ai/logos/critical-link.png)![Phytec](https://www.rapidflare.ai/logos/phytec.png)· Explore → ](https://www.rapidflare.ai/industry/manufacturers)[OEMs ### Your product expertise, wherever the buying decision happens You make the product, and you carry the deepest knowledge of it: specs, applications, firmware, compatibility, roadmap. Rapidflare turns that knowledge into agents that answer for your website, your sales team, and your channel, so the expertise scales past the people who hold it. · Explore → ](https://www.rapidflare.ai/industry-solutions/oems)[Distributors ### EMS, ODM and OEM customers, each served properly Distributors serve three kinds of customer and each one buys differently: an EMS quoting a bill of materials, an ODM team specifying a system for a design win, and an OEM working from a plain-language requirement. Rapidflare builds the catalog across your line card and gives each motion its own agent. ![Macnica Americas](https://www.rapidflare.ai/logos/macnica.png)· Explore → ](https://www.rapidflare.ai/industry/distributors)[System Integrators ### Bid on more jobs, and get there first Whoever comes back first with the right options, a clear technical explanation and a detailed proposal wins the job. We build the product catalog across every line card you carry, give you the product information management system you never had, and turn a requirement into a proposal today. That means faster deal velocity and a higher win rate, not necessarily a bigger deal. ![Sage Integration](https://www.rapidflare.ai/logos/sage.png)![Portal.io](https://www.rapidflare.ai/logos/portal.png)![Alibi](https://www.rapidflare.ai/logos/alibi.png)· Explore → ](https://www.rapidflare.ai/industry/system-integrators)[Semiconductor ### Thousands of parts, thousand-page datasheets, one accurate answer Selection guides, parametric tables, errata sheets, reference designs, and a part-numbering scheme only your own people can parse. Rapidflare reads all of it into a knowledge graph and answers the way an applications engineer would: from the application, with the datasheet page cited. · Explore → ](https://www.rapidflare.ai/industry-solutions/semiconductor)[Physical Security ### Support, sales and channel enablement from one vendor A channel business runs on the volume of deals it can bid and close, not on one large contract. Rapidflare answers the support question before it becomes a ticket, enables the sales team, and gives the channel the same technical depth as your own team. ![Brivo](https://www.rapidflare.ai/logos/brivo.png)![Eagle Eye Networks](https://www.rapidflare.ai/logos/eagle-eye.png)![Camden](https://www.rapidflare.ai/logos/camden.png)![Alibi](https://www.rapidflare.ai/logos/alibi.png)· Explore → ](https://www.rapidflare.ai/industry/physical-security)[Industrial Automation ### Check stock, cross-reference, configure, order Many of your components are configurable: the SKU does not exist until someone specifies it, and the requirement arrives as prose in an email or over the phone. Rapidflare checks live inventory first. If the part is in stock, it ships. If not, it finds a compatible part through cross-reference. If nothing matches, it runs the configuration tools and creates the SKU. Then it enters the order, with the right shipping details, into your ERP: the whole workflow, automated. ![Tolomatic](https://www.rapidflare.ai/logos/tolomatic.png)· Explore → ](https://www.rapidflare.ai/industry/industrial-automation)[Sensors and IoT ### From a deployment problem to the right sensor, gateway, and stack Your buyers describe environments: a cold-chain trailer, a plant floor, a remote site with no power budget. The right answer crosses sensing range, protocol, power, enclosure rating, and platform compatibility. Rapidflare reasons across all of it and shows why the recommendation holds. · Explore → ](https://www.rapidflare.ai/industry-solutions/sensors-iot)[Connectivity and RF ### From use case to antenna, without the buyer learning RF first A drone builder asks for fewer nulls. An asset tracker needs LTE and GNSS in one package on a tiny ground plane. The right part depends on bands, gain, pattern, connector, mounting, and the physics of where it sits. Rapidflare translates the use case into those constraints and answers with the datasheet open. · Explore → ](https://www.rapidflare.ai/industry-solutions/rf-connectivity)[B2B e-Commerce ### A buyer describes the job, the site returns a quote Keyword search cannot do anything with "I need pricing on rivets and hardware for a solar install we’re bidding on." Rapidflare clarifies the spec, filters the catalog, checks live inventory, substitutes what is out of stock, builds the BOM and generates the quote. ![Bay Supply](https://www.rapidflare.ai/logos/bay-supply.png)![McFadyen](https://www.rapidflare.ai/logos/mcfadyen.png)· Explore → ](https://www.rapidflare.ai/industry/b2b-ecommerce) What they share ## Different industries, the same underlying problem Too many products, too few people who can explain them. The expertise sits with a handful of engineers, and everything queues behind their calendar. The pattern - **The catalog holds a fraction of the knowledge.** The rest is in datasheets, application notes, reference designs, support tickets and schematics. - **The question does not arrive as a query.** It arrives as an application, a BOM, a site walkthrough or a photograph. - **The answer requires reasoning, not retrieval.** Matching a requirement to a product means understanding both. - **The people who can do it do not scale.** Application engineers are the bottleneck in every one of these businesses. What we build once - **A product intelligence layer.** We ingest your technical documentation and normalize it into a catalog and a knowledge graph. - **Agents on top of it.** Selection, technical support, cross-reference, proposal, order entry, each task-specific rather than general purpose. - **Deployed where the work happens.** Website, inside your product, partner portal, Slack, Teams, developer communities, ERP. - **With a source on every line.** Every answer traceable back to the document it came from. 30%+ Fewer L1 support requests in the AMD ROCm developer community 80% Of purchase order entry automated at Tolomatic, returning around 120 hours a month 17,882 Parts narrowed to three matching items in a single Bay Supply conversation Get started ## Bring your catalog and we’ll show you the agent on it Tell us the industry and the workflow you want to fix. We’ll build a working agent on your own product data and put it in front of you. [Book a demo](https://www.rapidflare.ai/contact) [See it by team](https://www.rapidflare.ai/by-team) SOC 2 Type II  ·  Every answer traceable to its source --- # For OEMs Source: https://www.rapidflare.ai/industry-solutions/oems > Rapidflare for OEMs: turn deep product knowledge into agents for your website, sales team, and channel. For OEMs # Your product expertise, wherever the buying decision happens You make the product, and you carry the deepest knowledge of it: specs, applications, firmware, compatibility, roadmap. Rapidflare turns that knowledge into agents that answer for your website, your sales team, and your channel, so the expertise scales past the people who hold it. [Book a demo](https://www.rapidflare.ai/contact) [All industries](https://www.rapidflare.ai/by-industry) Sound familiar? ## The OEM squeeze: everyone needs your experts, and there are three of them ### The channel dilutes your story Distributors and integrators sell your product without your depth, and the technical question comes back to you anyway, days later. ### Support absorbs your engineers The people who should be working on the next product spend their days answering questions the documentation already covers. ### Your website sells spec sheets A buyer arrives with an application and leaves with a PDF, because nothing on the site can reason from their problem to your part. What Rapidflare does here ## One knowledge layer, every audience answered 01 ### The catalog becomes a knowledge graph Datasheets, application notes, errata, and product relationships, read once and kept current, with every answer cited back to the document revision. 02 ### Your website answers applications, not keywords A buyer describes the job and the agent narrows your catalog the way your best application engineer would, with the reasoning shown. 03 ### The channel gets your depth without your headcount Distributor and partner audiences run on the same graph with their own access rules, so the channel answers correctly without another training cycle. 04 ### Support answers what it can prove and escalates the rest Documented questions get cited answers in seconds; the undocumented ones reach your engineers with the checks already done. Proof ## From companies shaped like yours [ 30% · Fewer Level 1 support queries Global access-control leader ### An access-control leader cut Level 1 support queries by 30% One agent grounded in a cleaned-up knowledge base now answers support teams, SaaS users, and resellers, powering 10,000 conversations a month. - Physical security and access control - Technical support - Sales - OEM ](https://www.rapidflare.ai/customers/access-control)[ 99,000+ · Authorized dealer and integrator product questions supported Cloud-managed video surveillance provider ### How a cloud-managed video surveillance solution provider made its product expertise instantly accessible across its dealer and integrator channel Authorized security dealers and integrators ask technical questions in natural language and get answers grounded in the company's own product knowledge. - Physical security and access control - Technical support - Sales - OEM ](https://www.rapidflare.ai/customers/alibi)[ 3 systems · DEEPX systems on one intelligence layer: technical support, engineering, and developer enablement DEEPX ### DEEPX put its SDK, repositories, and engineering docs behind one answer layer The NPU maker unified DXNN SDK documentation, GitHub repositories, and internal engineering systems into one cited answer layer for edge AI developers. - Semiconductor - Industrial and manufacturing - Technical support - OEM ](https://www.rapidflare.ai/customers/deepx) ## See your own catalog answering like your best engineer [Book a demo](https://www.rapidflare.ai/contact) [See the case studies →](https://www.rapidflare.ai/customers) --- # For connectivity and RF companies Source: https://www.rapidflare.ai/industry-solutions/rf-connectivity > Rapidflare for connectivity and RF companies: from use case to the right antenna or module, with the constraints made explicit. For connectivity and RF companies # From use case to antenna, without the buyer learning RF first A drone builder asks for fewer nulls. An asset tracker needs LTE and GNSS in one package on a tiny ground plane. The right part depends on bands, gain, pattern, connector, mounting, and the physics of where it sits. Rapidflare translates the use case into those constraints and answers with the datasheet open. [Book a demo](https://www.rapidflare.ai/contact) [All industries](https://www.rapidflare.ai/by-industry) Sound familiar? ## Why RF catalogs defeat their own buyers ### The buyer speaks application, the catalog speaks RF Bands, VSWR, radiation patterns. Most buyers cannot fill in your parametric filter, and the ones who try often fill it in wrong. ### Placement changes the answer Ground plane, enclosure, and mounting move performance, and that judgment lives with a handful of RF engineers. ### Every design win starts as an enquiry someone must triage Application questions queue behind a small team, and slow answers lose designs to whoever answered first. What Rapidflare does here ## What Rapidflare does on an RF catalog 01 ### Use case in, constraints out The agent turns the application into bands, gain, connector, and mounting requirements, asking only the questions that narrow the catalog. 02 ### Reads the RF documents properly Patterns, tables, and test conditions extracted at benchmarked accuracy, so the recommendation stands on the datasheet, not on a summary of it. 03 ### Honest about placement Where ground plane or enclosure will move the result, the agent says so and routes the design review to your engineers with context attached. 04 ### Answers at enquiry speed The first response goes out in seconds with sources shown, so your team enters the conversation at the interesting part. ## Bring your antenna catalog and a hard use case [Book a demo](https://www.rapidflare.ai/contact) [See the case studies →](https://www.rapidflare.ai/customers) --- # For semiconductor companies Source: https://www.rapidflare.ai/industry-solutions/semiconductor > Rapidflare for semiconductor companies: accurate, cited answers across dense parametric catalogs, from selection to support. For semiconductor companies # Thousands of parts, thousand-page datasheets, one accurate answer Selection guides, parametric tables, errata sheets, reference designs, and a part-numbering scheme only your own people can parse. Rapidflare reads all of it into a knowledge graph and answers the way an applications engineer would: from the application, with the datasheet page cited. [Book a demo](https://www.rapidflare.ai/contact) [All industries](https://www.rapidflare.ai/by-industry) Sound familiar? ## Where semiconductor sales and support leak time ### Parametric search assumes an expert It works when the buyer already knows the parameters. It does nothing for a system designer who starts from the application. ### The datasheet is not the whole truth The real answer often spans the datasheet, an app note, an errata sheet, and a reference design, and only your FAEs hold that join in their heads. ### Cross-references win and lose sockets When a competitor part comes up, the team that answers fastest with an honest comparison usually keeps the socket. What Rapidflare does here ## What Rapidflare does on a semiconductor catalog 01 ### Reads the documents engineers write Extraction built for parametric tables, package drawings, and revision marks, benchmarked at 95% extraction accuracy, with the scoring rule published. 02 ### Selection from the application down The buyer describes the system; the agent narrows by the parameters that decide it, asking only the questions that matter. 03 ### Cross-reference with the mismatch flagged Competitor part in, ranked equivalents out, with the differences named before the customer finds them. 04 ### Support that spans the document set Answers assembled across datasheet, errata, and app note, cited line by line, escalated with the work attached when silicon behaves strangely. Extraction accuracy, our benchmark - Rapidflare · · 95% - Contextual AI · · 62% - AWS Textract · · 49% [How we measured this](https://www.rapidflare.ai/methodology) Proof ## From companies shaped like yours [ 3 systems · DEEPX systems on one intelligence layer: technical support, engineering, and developer enablement DEEPX ### DEEPX put its SDK, repositories, and engineering docs behind one answer layer The NPU maker unified DXNN SDK documentation, GitHub repositories, and internal engineering systems into one cited answer layer for edge AI developers. - Semiconductor - Industrial and manufacturing - Technical support - OEM ](https://www.rapidflare.ai/customers/deepx) ## Bring a product family and watch it answer like an FAE [Book a demo](https://www.rapidflare.ai/contact) [See the case studies →](https://www.rapidflare.ai/customers) --- # For sensors and IoT companies Source: https://www.rapidflare.ai/industry-solutions/sensors-iot > Rapidflare for sensors and IoT companies: from deployment requirements to the right device stack, with the reasoning shown. For sensors and IoT companies # From a deployment problem to the right sensor, gateway, and stack Your buyers describe environments: a cold-chain trailer, a plant floor, a remote site with no power budget. The right answer crosses sensing range, protocol, power, enclosure rating, and platform compatibility. Rapidflare reasons across all of it and shows why the recommendation holds. [Book a demo](https://www.rapidflare.ai/contact) [All industries](https://www.rapidflare.ai/by-industry) Sound familiar? ## Why IoT catalogs are hard to buy from ### The product is a system, not a SKU Sensor, gateway, connectivity, and platform have to work together, and the compatibility truth lives across four document sets. ### The requirement arrives as an environment Temperature, mounting, interference, battery life. Filters cannot parse a site description; your best sales engineer can. ### The channel sells breadth it cannot explain Resellers carry your line without your depth, so deployment questions stall deals or come back to your support queue. What Rapidflare does here ## What Rapidflare does on a sensors and IoT catalog 01 ### System-level answers The graph holds device, gateway, and platform relationships, so the agent recommends a stack that works together and says why. 02 ### Environment in, specification out The buyer describes the deployment; the agent translates it into range, protocol, power, and enclosure constraints, asking only what narrows the choice. 03 ### Support before the ticket Provisioning, firmware, and integration questions answered from your documentation with citations, around the clock. 04 ### The channel answers like your own team Partner audiences run on the same graph with scoped access, so a reseller quotes the right stack the first time. ## Describe a deployment and watch it spec the stack [Book a demo](https://www.rapidflare.ai/contact) [See the case studies →](https://www.rapidflare.ai/customers) --- # B2B e-Commerce Source: https://www.rapidflare.ai/industry/b2b-ecommerce > Keyword search cannot handle a described job. Rapidflare clarifies the spec, filters the catalog, checks inventory, swaps stock-outs, and generates the quote. B2B e-Commerce # Your buyer knows the job, but not the part number Keyword search cannot do anything with "I need pricing on rivets and hardware for a solar install we’re bidding on." Rapidflare clarifies the spec, filters the catalog, checks live inventory, substitutes what is out of stock, builds the bill of materials and generates the quote. [Partner with us](#partners) Who buys · The customer experience owner: CMO, digital experience, and digital marketing They care about · B2B commerce experience and site conversion rate Also for · Design consultants and commerce partners building storefronts for their clients Built with · Bay Supply · McFadyen Watch it work ## One conversation, from a described job to a priced quote Bay Supply’s Rapid Product Selector, live and powered by Rapidflare. 01 · Log the request · Solar Co. · 15,000 rivets / 6,000 inserts · need-by Aug 15 02 · Clarify the requirements · Only what changes the answer: material thickness, coastal or inland, quantity split across sites 03 · Find matching parts · 17,882 parts filtered to three matching items 04 · Check inventory availability · Two of three in stock, the pneumatic rivet tool is unavailable 05 · Find an alternative part · Substituted a same-CFM model that is in stock and ships same day 06 · Build the bill of materials · Four line items, split across three sites 07 · Create the quote · Priced per site with freight and lead time, and reasoning clearly stated Why it converts ## It ends at a transaction, not just an answer Every other product-discovery tool hands the buyer a list and hopes. This one hands them a quote. What is different - **The agent shows its work.** The side panel is a live audit trail: every step, decision, and why. Explainability rendered as interface rather than asserted as a claim. - **A stockout becomes a substitution, not a lost order.** Cross-reference runs automatically against live inventory, so "unavailable" does not end the conversation. - **It clarifies rather than interrogates.** Only the questions that change the answer, presented as options a buyer can tap. - **It reasons over the full catalog,** not the subset your search index happens to cover well. What it plugs into - **Your commerce platform’s product APIs,** including Adobe Commerce, where we work from the product and search endpoints and the rich attribute data behind them. - **Live inventory,** so availability and substitution are real rather than advisory. - **Your quoting experience,** including add-to-quote, quote summaries and retrieving a buyer’s existing quotes through the conversation. - **Your CRM,** so the resulting lead or quote lands where your team already works. Who buys · The customer experience owner: CMO, digital experience leaders, and often digital marketing, since they design the site What they measure · Conversion rate, quote volume, average order value, self-service rate What it replaces · Keyword search, faceted navigation dead-ends, and a contact form For agencies and implementation partners ## Building an e-commerce site for your customer? Talk to us If product discovery and quoting are in your scope, we should be in your stack. We work with the partners who build these storefronts, not around them. What you get ### A differentiator you can sell Natural-language product selection and quoting is the capability your client is asking for and the platform does not ship. It changes the shape of the proposal. How we work ### Inside your delivery We integrate against the platform APIs you are already building on and fit into your implementation, rather than arriving as a separate vendor with a separate timeline. The model ### McFadyen An Adobe Gold Solution Partner who brought Rapidflare into the storefronts they build, including Bay Supply. We want more partners like them. [Become a partner](https://www.rapidflare.ai/contact)[Talk to our team](https://www.rapidflare.ai/contact) Questions we get ## Common questions How is this different from AI site search? Site search returns results, whereas Rapidflare returns a quote. The chain runs discovery, spec clarification, catalog match, live inventory check, substitution where something is out of stock, bill of materials, then a priced quote with freight and lead times, in one conversation, with the reasoning shown throughout. What if our catalog attributes are inconsistent? Normalizing the catalog is part of the work, and it is why the recommendations are accurate. We pull the product and attribute data from your commerce APIs and structure it into a product intelligence layer before any agent sits on top of it. What happens when an item is out of stock? The agent finds an equivalent and carries it into the quote, telling the buyer what it substituted and why: for example, a different model with the same rating that is in stock and ships same day. That is an order you would otherwise have lost at the availability check. Can it create quotes in our system, not just display one? Yes. We integrate with your quoting experience: add-to-quote, quote summary, and retrieving a buyer’s existing quotes through the conversation, and customize what the add-to-quote action does per customer. We are an agency. How does this work commercially? Talk to us. We work with implementation and design partners who bring Rapidflare into the storefronts they build, and we are actively looking to add more. Keep reading ## Related [By Team ### Marketing Getting found, converting what arrives, and the content gap report. ](https://www.rapidflare.ai/team/marketing)[By Industry ### Distributors When the same catalog also has to serve EMS and ODM customers. ](https://www.rapidflare.ai/industry/distributors)[By Industry ### Manufacturers Product selection on a manufacturer’s own site. ](https://www.rapidflare.ai/industry/manufacturers) Get started ## Point it at your storefront Give us access to your product APIs and we’ll build a working selector on your real catalog: inventory, substitutions and quoting included. [Book a demo](https://www.rapidflare.ai/contact) [Back to all industries](https://www.rapidflare.ai/by-industry) SOC 2 Type II  ·  Every answer traceable to its source --- # Distributors Source: https://www.rapidflare.ai/industry/distributors > A distributor's catalog spans many suppliers and many kinds of customer. Rapidflare builds the catalog across your line card and gives each motion an agent. Distributors # EMS, ODM and OEM customers each buy differently A distributor’s catalog spans many suppliers, and the customers on the other side of it are running very different businesses. Rapidflare builds the product catalog across your line card and gives each motion the agent it needs. [See customer stories](https://www.rapidflare.ai/customers) Who buys · VP of Sales. This is a sales-driven purchase. Who uses it · Inside and field sales, field application engineers, customer support, and your customers, where you choose to expose it Customer types · EMS · ODM and design win · OEM Deployed with · Macnica Americas Where the value lands ## Two places, and they don’t behave the same way Most distributors start internal and expand outward. Both run on the same product intelligence layer. Internal: your sales and support teams - **We integrate with the knowledge sources your teams already rely on:** Confluence, Jira, knowledge base, PIM and ERP. - Responses to pre-sales and post-sales queries get faster and more accurate, without routing through a specialist. - **Sales ramp-up time drops significantly.** No rep can hold every vendor’s portfolio in their head, which is why onboarding takes so long today. External: your customers - **Product selection on your site,** guiding customers through pre-sales inquiries the way an inside salesperson would. - **Technical support** across the lines you carry. - **Custom agentic workflows:** for example turning an incoming email request into a quote, integrated with your ERP or CPQ. Three customer motions ## Same catalog, three different jobs for the agent They share catalog complexity and nothing else. The workflows, the buying triggers and the winning move are distinct, so the agents are too. Motion 01 · EMS ### Answer the BOM, fast and correctly An electronics manufacturing services customer sends a bill of materials. You need to understand it, identify the components, find alternatives, cross-reference parts, check availability and sourcing, then come back. The hard part isn’t finding an alternate part, it’s finding one that doesn’t break the integrity of the overall design. A substitution creates downstream dependencies, so cross-reference has to understand related components, technical compatibility, design constraints and the possibility of multiple substitutions at once. How quickly and how accurately you respond to that BOM directly affects how quickly you win the business. BOM → cross-reference → alternatives → validation → sourcing recommendation Motion 02 · ODM and design wins ### From a system requirement to a technical proposal Your sales and application teams work with electronics companies at a high technical level: system requirements, architecture, the customer’s application, then the component requirements that follow from it. The goal is to produce a technical proposal strong enough to get designed in, with as much of your line card in the design as the application justifies. Rapidflare takes a high-level requirement and builds a system-level representation, generates the block diagram, identifies the components required, recommends parts from the lines you carry and drafts the proposal. Requirement → system architecture → block diagram → component selection → technical proposal Motion 03 · OEM and general distribution ### A plain-language requirement, resolved to a SKU Not every distributor has a sophisticated PIM or a detailed technical product database. Plenty run on a line card, supplier websites, datasheets, basic product listings, and individuals’ knowledge. So when a customer says "I need a marine rivet that’s waterproof, airtight, corrosion-resistant and rated to this pressure," a salesperson has to interpret the requirement, search supplier sites, open datasheets, compare products, sometimes call the supplier, and eventually land on a SKU. Rapidflare can normalize your line card into a real product catalog and compress that hunt into one conversation. Plain-language requirement → technical reasoning → product recommendation Multi-vendor by design ## One agent per line, not one agent for everything A distributor’s catalog is really dozens of catalogs, each with its own conventions. An agent that blurs them together isn’t what the customer needs. How we structure it - **You get a selling agent per supplier line,** so a question about one vendor’s portfolio is answered from that vendor’s documentation. - **Technical support agents** cover the lines where the support burden justifies one. - **Your own products and IP** get their own agent, separate from the supplier lines you distribute. - Sources are named and namespaced per vendor, so nothing leaks across a boundary that matters commercially. Why it matters - **Supplier relationships are contractual.** Vendor content stays inside vendor scope. - **Accuracy improves** when the agent is not reasoning across three vendors’ conflicting terminology at once. - **You can add a line without rebuilding:** a new supplier is a new hub, not a migration. - **Usage is visible per line,** which is useful evidence in a supplier conversation. Deployed with · Macnica Americas Macnica runs product selection agents across their supplier line card, a separate selling agent per vendor, plus technical support agents on several product lines, used day to day by their own sales teams and field application engineers. Outcomes ## What moves Speed · Response time on BOMs, RFQs and technical questions, the thing that decides who wins the business Quality · Better technical recommendations and stronger proposals, from teams that cannot know every vendor line Scale · Sales ramp-up time, and the number of opportunities a team can carry without adding headcount Design wins get decided by whoever puts a credible technical answer in front of the customer first. For a distributor, that is a response-time problem long before it is a product problem. Questions we get ## Common questions from distributors We carry hundreds of supplier lines. Where do we start? With the lines that generate the most technical inquiry, not the most revenue: they are rarely the same list. We stand up a hub per line, so you can start with three and add the rest as the value is proven. Nothing about the first three constrains the next thirty. What if we don’t have a PIM, or ours is incomplete? That is common, and it is a large part of the work. We build the product catalog across your line cards from supplier documentation and whatever structured data exists, and normalize it. For many distributors this is the first time the line card has existed as a queryable product database. How does cross-reference avoid recommending a part that breaks the design? By reasoning over relationships rather than matching a spec row. The agent looks at related components, technical compatibility and design constraints, and where a substitution has downstream implications it says so instead of returning a confident single answer. Anything it cannot resolve is surfaced rather than guessed. Can we expose this to our customers, or is it internal only? Either. Most distributors start internal with sales and support, then expose product selection externally once they are confident in the answers. The same layer serves both, with different scope. What if our suppliers are sensitive about their content? Understood, and it is the reason for the per-line architecture. Each supplier’s material sits in its own hub with its own sources, and the agent for one line does not reason over another’s documentation. Keep reading ## Related [By Team ### Sales Ramp time, response time, and reps who can answer across every line. ](https://www.rapidflare.ai/team/sales)[By Industry ### Manufacturers The other side of the same channel relationship. ](https://www.rapidflare.ai/industry/manufacturers)[By Industry ### B2B e-Commerce When the requirement should end in a quote on your storefront. ](https://www.rapidflare.ai/industry/b2b-ecommerce) Get started ## Start with three lines Tell us which supplier lines generate the most technical inquiry and we’ll build agents on them, so you can judge the answers before you commit. [Book a demo](https://www.rapidflare.ai/contact) [Back to all industries](https://www.rapidflare.ai/by-industry) SOC 2 Type II  ·  Every answer traceable to its source --- # Industrial Automation Source: https://www.rapidflare.ai/industry/industrial-automation > Actuators, drives and motion components are specified, not picked off a shelf. Rapidflare reads the requirement, configures the part, and enters the order. Industrial Automation & Motion Control # The part number often does not exist yet: it has to be configured Actuators, drives and motion components are not picked off a shelf, they are specified. Rapidflare reads the requirement in plain text, runs the config, and creates the SKU in your system. Then, it takes the purchase order and enters it into your ERP. [See customer stories](https://www.rapidflare.ai/customers) Who buys · IT Director Solutions · Product selection with configuration · technical support · automated order entry Systems · SAP, SyteLine and other ERPs · CRM · configuration and spec tools Deployed with · Tolomatic 01 · Product selection ## Product selection, where the SKU has to be built Many of the components you carry are configurable. There’s no fixed part sitting in a catalog waiting to be found, someone has to specify it. How the requirement arrives - **As natural language.** A customer describes their specification in an email or over the phone, not as parametric fields. - **As an image.** A photo or drawing, followed by a "what’s compatible with this?" query. - Someone interprets it, looks it up, and runs the configuration and spec tools before quoting anything. What Rapidflare does - **Reads the spoken/written specification** and deciphers what is being asked for. - **Runs the configuration and spec tools** as part of the conversation, instead of handing it off to a person. - **Recommends the right part or creates the configured SKU** directly in SAP or the CRM. - **Answers from an image,** identifying any compatible parts. There’s no existing part number to look up. Someone has to specify it, every time. 02 · Order entry ## Once the order arrives, it stops being typed in by hand Tolomatic processes over 1,400 purchase orders a month, which took around 150 hours of manual entry into SyteLine. Purchase orders arrive by email from distributors, direct customers and Tolomatic’s own storefront, and no two customers lay one out the same way. Historically that meant a person reading a PDF and typing it in: looking up the customer, matching part numbers, resolving the ship-to address, entering it, one order at a time. It doesn’t scale or tolerate the real-world mess of purchase orders: embedded-image PDFs instead of text, non-standard SKU columns, several separate orders bundled into a single email. ### Any system can read a PO. The harder part is knowing when to stop and hand it to a person This system writes into a live order pipeline, so every order passes four independent validation checks before anything is created. 01 · Customer identity · Matched by email domain, with a name/zip/address fallback for accounts holding multiple IDs 02 · Shipping · Every ship-to checked against your own defined list, and never created automatically 03 · Product · Every line-item code and quantity validated against what is orderable 04 · Pricing · Checked against, never written in: the PO doesn’t have your real discount rules · Exceptions · Anything unresolved routes to Sales or IT. 80% Of order entries automated 120 hrs Returned to the team every month 0 Orders written on an unresolved exception How it gets deployed ## Staged, against real order traffic Nobody should flip a switch on a system that creates customer orders. We prove each stage on live traffic before expanding scope. Stage 01 ### Manual-assisted extraction Narrow scope, submitted by hand, so extraction and validation logic can be proven against real orders before automation. Stage 02 ### Automated flow Orders are picked up and processed automatically within a limited scope. Running against live traffic is what surfaces the formatting problems a generic PO parser misses. Stage 03 ### Production Full deployment, with exceptions still routing to a person. Tolomatic went from kickoff to a board-level demo of the complete flow in roughly four months. It removes the repetitive work, not the judgment calls, so the team spends their time on the orders that need a person. 03 · Technical support ## Technical support, on the same product knowledge Sizing questions, compatibility, installation, troubleshooting, answered from your documentation, on your site, in your product or inside Slack and Teams for your own team. The same catalog that drives selection drives support. Deployed with · Tolomatic Tolomatic can be referenced for product selection. The order entry system runs against their live SyteLine order pipeline. Questions we get ## Common questions from automation companies Our products are configured, not selected from a list. Does that work? Yes, that works. The agent interprets the natural-language specification, runs your tools as part of the conversation, and either recommends the right part or creates the configured SKU in SAP or your CRM. What if our ERP doesn’t have a clean API for order creation? This is a common occurrence. SyteLine for example, exposes no single unified API for order creation: it took working across multiple REST endpoints and IDO methods with an incomplete attribute set. Accurate extraction still has to be stitched into the ERP carefully, and that integration work is part of what we deliver. What happens with a badly formatted purchase order? Most orders are this way. We handle line items delivered as scanned images rather than text, customers whose "SKU" column is not the part number, and single emails containing several separate orders. Where a value cannot be resolved, an unrecognized ship-via for instance, it routes to review rather than guessing the nearest match. How do we know it will not create a wrong order? Four independent validation checks run before anything is written, pricing is never written in directly, no new ship-to address is ever created automatically, and any unresolved exception routes to Sales or IT. The system is designed around knowing when to stop. Can a customer just send a photo of a part? Yes. Image-based compatibility lookup is supported: a customer sends a photo or drawing and asks what is compatible, and the agent answers from your catalog. Keep reading ## Related [By Industry ### Manufacturers Product selection and channel enablement for component makers. ](https://www.rapidflare.ai/industry/manufacturers)[By Team ### AI Enablement The ingestion pipeline, evals and safeguards behind a system that writes to your ERP. ](https://www.rapidflare.ai/team/ai-enablement)[By Team ### Sales What changes for the people quoting configured products. ](https://www.rapidflare.ai/team/sales) Get started ## Send us thirty purchase orders We’ll run them through extraction and validation and show you exactly what we get right, what we flag, and why. [Book a demo](https://www.rapidflare.ai/contact) [Back to all industries](https://www.rapidflare.ai/by-industry) SOC 2 Type II  ·  Every answer traceable to its source --- # Manufacturers Source: https://www.rapidflare.ai/industry/manufacturers > Product selection that behaves like a sales engineer: it understands the use case, asks the right technical questions, and lands on a part number. Manufacturers # Your product knowledge shouldn’t depend on one application engineer’s calendar Rapidflare gives manufacturers a product selection experience that behaves like a sales engineer: understanding a high-level use case, asking the right technical questions, and arriving at a part number with the reasoning shown. [See customer stories](https://www.rapidflare.ai/customers) The problem ## Parametric search only covers a sliver of the spec It works when the customer already knows the parameters, or knows clearly what they want. It goes silent the moment someone describes a use case in natural language, an application, not a specification, which is exactly where the hard, valuable questions live. What your customer really asks - **"I need a component with these specific parameters."** Your existing product selector handles this well. - **"I’m designing an automotive infotainment system. What should I use?"** Nothing on your site can answer this. It requires contextual technical reasoning. - So the customer opens a ticket, emails a rep, or fills in a contact form and waits. Why it takes days - Your product catalog holds a subset of the technical knowledge that lives in datasheets, application notes and reference designs, which can get complex. - Answering properly means pulling in a sales engineer, an application engineer or a product specialist. - Long-tail customers never get that attention at all, so the design win goes to whoever answered first. Someone at your company can already answer almost any application question. The problem is there’s one of them, and every inquiry queues behind the same few people. What Rapidflare does ## An agent that reasons like your best application engineer It asks the clarifying questions a senior application engineer would ask, then narrows thousands of products down to the ones that fit. 01 ### Guided product selection The agent takes a high-level use case, asks the relevant technical questions, narrows the requirement, and reasons across your product information to identify suitable parts, then explains why, then cites its source inline. When an answer relies on a document you own, Rapidflare cites that document directly. And when the answer depends on a diagram embedded in a PDF, our Visual Reasoning Engine understands the diagram itself, rather than discarding it during ingestion. Application requirement → clarifying questions → shortlist → recommendation with reasoning 02 ### Technical support Register maps, pinouts, power sequencing, SDK integration, hardware and software bring-up: these are the questions your FAEs repeatedly answer, and every one of them is already documented somewhere. Deployed on your docs site, in your developer community, or inside your product. In the AMD ROCm Discord and Discourse community it cut L1 support requests by more than 30%. 03 ### Channel and partner enablement The same agent, pointed at your distributors, channel partners and resellers, so partners can answer for your products as well as your own team does, instead of defaulting to whichever line they know best. One live example: a manufacturer’s agents running inside a distributor’s own sales team, day to day, answering questions their reps would otherwise escalate back to the factory. 04 ### Competitive comparison and cross-reference Customers ask this unprompted. In live conversation logs, we see queries like “What’s your equivalent to this competitor’s part?” The agent reads both catalogs side by side, shortlists the closest matches, and builds the spec-by-spec comparison. The same capability lets your own reps defend a socket without waiting for a competitive analysis. 05 ### Technical proposals Once the parts are selected, the agent generates the technical recommendation or proposal the customer can act on, assembled from your own documentation rather than a template. Deployment ## Three ways manufacturers deploy it AMD runs all three. Knowledge Hub 1 ### Internal enablement Your own sales teams, application engineers, product specialists and support teams, behind single sign-on, with access to internal and pre-release material the public agent never sees. Knowledge Hub 2 ### Partner enablement Provided to your distributors, channel partners and resellers so they can sell your products with the technical depth of your own team. Knowledge Hub 3 ### Website and long-tail customers Deployed on your public site, so customers find the right product without a human sales engineer in the loop for every inquiry, including the long-tail customers who would never have gotten that engineer’s attention at all. Also deploys to · Docs and blog widgets And · Developer communities: Discord and Discourse And · Slack and Teams for internal use And · The site search bar Outcomes ## What moves 30%+ Reduction in L1 support requests, AMD ROCm developer community 80-90% Of basic installation and runtime developer questions targeted for resolution without a human ~90% Accuracy on a challenging certification question set during evaluation KPIs this touches - Time to technical response - Application-engineering workload and dependency - Product discovery and website conversion - Qualified opportunities created - Design-win velocity - Channel partner productivity How AMD got there - **Shadow production testing first.** Two weeks running against real Discord and forum questions, with responses monitored and ranked internally before anything went live. - **An admin dashboard ran alongside it.** Their team reviewed conversations and performance analytics throughout. - **Then expansion by surface:** guided selection for embedded and FPGA, support agents for FPGA and x86 embedded processors behind AMD single sign-on, and the ROCm developer community. Deployed with · AMD · · Qorvo · · Taoglas · · Critical Link · · Phytec Taoglas and Qorvo run Rapidflare on their public sites. Critical Link runs it in the site search bar. AMD runs it across four separate deployments including the ROCm developer community. Questions we get ## Common questions from manufacturers We already have a parametric product selector. Why add this? Parametric search is a filter: it needs the customer to already know the parameters. Rapidflare handles the case where the customer knows their application but not the specification, which is the inquiry that currently goes to an application engineer. The two work together: most customers who can use your existing selector should keep using it. What if our product catalog doesn’t contain everything in our datasheets? That is the normal starting position. We ingest the datasheets, application notes, reference designs and support history alongside the catalog, and structure all of it into one knowledge graph, so the agent can reason over material that was never in the PIM. What about specifications that only exist inside diagrams? Conventional retrieval flattens documents into text at ingestion and discards the diagrams, which means specifications inside schematics, timing charts and mechanical drawings never reach retrieval at all. Our Visual Reasoning Engine reconstructs and indexes those visuals so the agent can reason over them directly. How do we know it is not making things up? Every output is traceable to the document it came from, so your engineers can open the source and check. Beyond that, we run a practical evaluation framework against real traffic, and we typically start customers in a shadow mode where the team reviews responses before anything is exposed. Can our channel partners use it? Yes. You can provision the agent to distributors and resellers so they answer for your products with your technical depth, which directly affects whether a partner leads with your line or someone else’s. [By Team ### Sales How reps and FAEs use it day to day, and why ramp time drops. ](https://www.rapidflare.ai/team/sales)[By Team ### Marketing Product discovery, on-site conversion and the content gap report. ](https://www.rapidflare.ai/team/marketing)[By Industry ### Distributors What changes when the catalog spans many suppliers instead of one. ](https://www.rapidflare.ai/industry/distributors) Get started ## See it on your own products Send us your public documentation and we’ll build a working selection agent on your catalog before the first call. [Book a demo](https://www.rapidflare.ai/contact) [Back to all industries](https://www.rapidflare.ai/by-industry) SOC 2 Type II  ·  Every answer traceable to its source --- # Physical Security Source: https://www.rapidflare.ai/industry/physical-security > Security manufacturers and cloud platforms sell through partners, deal by deal. You win on volume of bids, which is where an agent earns its keep. Physical Security # A channel business runs on deal throughput, and so does everything we do for it Security manufacturers and cloud platforms sell through partners, deal by deal. You win on volume of bids, which is where an agent earns its keep. [See customer stories](https://www.rapidflare.ai/customers) Ideal buyer · CRO, marketing and support Also buys · VP Sales, VP Marketing, technical support leadership Lands with · Technical support Deployed with · Brivo, Eagle Eye Networks, Camden, Alibi The shape of the business ## Volume in every direction: deals, partners, questions The economics reward volume and speed, and each deal carries technical questions from a partner or an end customer. What that means operationally - **You sell through a partner channel,** so the people representing your products do not work for you. - **Deals are hundreds of thousands:** you churn out more rather than assessing a few. - Every deal needs bidding on, which means answering integration, compatibility and configuration questions quickly. - Support volume grows with the install base, and it grows faster than you can hire. Why this fits - **The questions repeat.** Installation, configuration, integration, and compatibility dominate tier-one volume. - **The answers exist.** They are in your documentation, your support history, and your compatibility matrices. - **The channel needs the same answers your own team does,** and today they queue for them. - Solving it once solves it for support, sales, and partners at the same time. What Rapidflare does ## Three jobs, one platform, one vendor Technical support is the front door. Sales enablement and partner enablement run on the same product knowledge, pointed at different audiences. 01 ### Technical support, embedded in your product Not a widget bolted to a help center: the agent goes inside the SaaS product itself, as the first responder to any support question a customer asks. Today it handles around 30% of support questions end to end, with no human involved. Roughly 90% of the question volume is answerable as coverage expands, and that gap is a content and ingestion problem we work through with you month by month. The result is many hours saved for the technical support team, and a better experience for the customer, who gets an answer immediately instead of waiting in a queue. 02 ### Sales enablement We run the sales enablement layer for security companies: your reps answering integration and compatibility questions in the room, building the technical case, and ramping onto new product lines in weeks instead of the usual six months. Questions like "does this camera work with that VMS?" and "which controller works with this door hardware?" stop being escalations. 03 ### Partner enablement Because the model is channel-led, enabling your sales team and partners is the same capability pointed at two audiences, and the second one is usually the bigger prize. Deployed in the partner portal, it gives dealers and integrators the technical depth of your own team, so they can specify and quote your products without waiting on your engineers. 04 ### Content analytics Alongside the agent, we hand back analytics on what your documentation is missing and what conversations people are having on the platform, then help you continuously improve the content behind it. Deployment ## Four surfaces, all live today Different audiences, different knowledge scope, one platform behind all of them. Surface 01 ### Embedded in your product The first responder to any support question, inside the software your customers already have open. Eagle Eye Networks and Brivo both run this. Surface 02 ### Partner portal Your dealers and integrators self-serving the technical answers they email your team for. Surface 03 ### Slack and Teams Your own people, in the tools they already work in, without another tab to remember. Surface 04 ### Your website Customers and prospects, answered before the question becomes a ticket or a lost opportunity. Knowledge scope ### Different hubs per audience Confidential and pre-release material sits in the internal hub and nowhere near the public one. Escalation ### Straight to a human A one-press hand-off from the conversation into your support queue or a live agent, configured to your workflow. Outcomes ## What moves ~30% Of support questions handled entirely by AI today, with no human involved ~90% Of question volume answerable as coverage expands 1 vendor Covering technical support, sales enablement and partner enablement Documentation gaps compound. Close them steadily and next quarter’s deflection rate automatically beats this quarter’s. Deployed with · Brivo · · Eagle Eye Networks · · Camden · · Alibi Questions we get ## Common questions from security companies Why does the CRO care about a support tool? Because it is not one. The same product knowledge answers the customer’s support question, arms your reps in a deal, and enables the channel to sell without your engineers. A CRO owns all three, which is why they are the cleanest buyer: one signature covers the whole surface. Can it really go inside our product, not just our website? Yes, and that is where it works best. Embedded in the product, the agent is the first thing a customer meets when they hit a problem, rather than something they would have to leave the product to find. Both Brivo and Eagle Eye Networks run it this way. What about our channel partners, who have different needs? They get their own deployment, usually in the partner portal, scoped to what partners should see. It is the same capability that enables your direct team, which is the point: in a channel-led business those are the same problem. How do you keep unreleased products out of customer-facing answers? Multiple agents across multiple knowledge hubs is a core part of the platform. Your internal support team’s hub can include confidential and pre-release material; the public agent’s hub cannot. The boundary is architectural, not a prompt instruction. What do we get besides the agent? Analytics on document gaps and on the conversations happening on your platform, plus ongoing work with you to close those gaps. That’s usually the part customers didn’t expect going in. Keep reading ## Related [By Team ### Support The two-tier model, and what happens to escalated tickets. ](https://www.rapidflare.ai/team/support)[By Industry ### System Integrators The partners installing your products, and how they bid. ](https://www.rapidflare.ai/industry/system-integrators)[By Team ### Sales Ramp time and technical confidence in the field. ](https://www.rapidflare.ai/team/sales) Get started ## Point it at your documentation We’ll ingest what you have, show you the answers it produces, and tell you what your documentation is missing. [Book a demo](https://www.rapidflare.ai/contact) [Back to all industries](https://www.rapidflare.ai/by-industry) SOC 2 Type II  ·  Every answer traceable to its source --- # System Integrators Source: https://www.rapidflare.ai/industry/system-integrators > We build the catalog across every line card you carry, give you the product information system most integrators lack, and turn a requirement into a proposal. System Integrators # Whoever gets the proposal out first, with the right options, wins the job We build the catalog across every line card you carry, give you the product information system most integrators lack, and turn a requirement into a proposal. [See customer stories](https://www.rapidflare.ai/customers) Who buys · Operations, the person who manages the bids and carries the project P&L Who uses it · Bidders, sales teams and technicians. Internal, not customer-facing. Lands with · The proposal and bill of materials agent Expands to · Cross-reference, technical support, order operations How the work arrives ## Two paths in, one thing that decides the outcome Whether it came from a formal process or a site walkthrough, the job goes to whoever comes back first with the right options and a proposal that explains itself. The formal path - **An RFP** on the larger jobs: a structured response, on a deadline, against competitors doing the same thing. - Volume matters as much as quality: the more RFPs you can respond to properly, the more you win. The informal path - **A site walkthrough** on smaller commercial and residential work: a requirement captured in someone’s notes and turned into a quote. - It’s a faster cycle, with a thinner margin. Where the time goes - **Most integrators have no PIM at all.** Nothing normalizes product data across the manufacturers on your line card. - Every proposal gets rebuilt from scratch, working across vendor sites and datasheets to figure out what you can sell that matches. - Managing the line cards themselves is a job nobody owns: products change, and the knowledge lives with whoever last quoted them. - **The constraint on winning more work is quoting speed and quoting volume,** not sales effort. What costs you these jobs is being late to respond, with a proposal that reads like it was assembled in a hurry. What Rapidflare does ## The catalog you’re missing, and the proposal you don’t have time to write 01 ### A product catalog across every line card We build the catalog across all the manufacturers you carry and give you a working product information layer: normalized, queryable, and maintained. For most integrators this is the first time the line card has existed as a real product database rather than a folder of PDFs and a set of supplier logins. 02 ### Requirement to proposal When a requirement comes in from a customer, an RFP document or notes from a site walkthrough, we match it against what you can sell, assemble the options, and put together the proposal and the bill of materials. The result is more RFPs answered faster. Response velocity and volume both move and convert. Requirement → match to line card → options → BOM → detailed proposal 03 ### Quote to fulfillment, end to end An order arrives by email with a PDF and some loose requirements. The agent reads it, checks whether the part is in your CRM and your inventory, and when it is not, cross-references a substitute from the knowledge graph. It re-checks the CRM and CPQ, then sends the quote. When a purchase order comes back, it places the orders with your distributors automatically and returns to the requester with shipping dates, tracking and confirmation. Email + PDF → inventory check → cross-reference → CPQ → quote → PO → distributor orders → tracking 04 ### Technical support for your own team Technicians asking product questions across hundreds of products from dozens of manufacturers get answered from the same catalog. Outcomes ## What moves Velocity · How quickly a requirement becomes a sendable proposal. Volume · How many RFPs and quotes the same team can respond to. Win rate · Rises when you show up first with the right options and a clear explanation. Deployed with · Sage Integration · · Portal.io · · Alibi Questions we get ## Common questions from integrators We do not have a product database. Is that a blocker? It is the opposite: it is most of the value. We build the catalog across your line cards from manufacturer documentation and whatever you already hold, and normalize it into a product information layer. You end up with the PIM as a by-product of getting the proposal agent working. Do our customers interact with this? No. For integrators this is an internal tool. Your bidders, sales team and technicians use it, and your customers see the output, a faster, better proposal, without ever touching the agent. What happens when a part we quoted is not available? The agent cross-references a substitute from the knowledge graph, re-validates it against your CRM and CPQ, and carries it into the quote. Where it cannot find an equivalent it flags the line rather than silently swapping something in. Can it place orders with our distributors? Yes, once a purchase order is received. It places the orders and comes back to the requester with ship dates and tracking. As with every write action we take, anything unresolved routes to a person instead of being guessed. How long before we can quote with it? It depends on how many line cards are in scope and what documentation exists. We normally start with the manufacturers behind the majority of your bids, which gets a usable catalog in place, then extend from there. Keep reading ## Related [By Industry ### Physical Security The manufacturers and platforms whose products you install. ](https://www.rapidflare.ai/industry/physical-security)[By Team ### Sales What changes for the people writing the bids. ](https://www.rapidflare.ai/team/sales)[By Industry ### Distributors Cross-reference and sourcing, from the other side. ](https://www.rapidflare.ai/industry/distributors) Get started ## Bring us your line card We’ll build the catalog across your manufacturers and show you a proposal generated from a real requirement. [Book a demo](https://www.rapidflare.ai/contact) [Back to all industries](https://www.rapidflare.ai/by-industry) SOC 2 Type II  ·  Every answer traceable to its source --- # By Team Source: https://www.rapidflare.ai/by-team > Rapidflare for sales, marketing, support, AI enablement and bidding teams. One product intelligence layer, five teams that stop waiting on each other. By Team # One product intelligence layer, five teams that stop waiting on each other The reason technical questions take days is not that nobody knows the answer. It is that the answer lives with someone else. Rapidflare puts your product knowledge where each team already works, and gives every team its own view of it. [Book a demo](https://www.rapidflare.ai/contact) [See it by industry](https://www.rapidflare.ai/by-industry) 5 teams ## Pick the team with the worst bottleneck Each page covers what that team is accountable for, what slows them down today, exactly what changes, and what the leader sees on their numbers. [Sales ### Answer the customer, instead of going back to the factory Every question a rep cannot answer means working through application engineers, product managers and architects before anyone can respond. The customer waits on your org chart. Rapidflare puts the answer in the rep’s hands, and gets a new rep productive fast. Field sales · AEs · sales engineers · FAEs · channel account managers · Explore → ](https://www.rapidflare.ai/team/sales)[Marketing ### Get found, convert what arrives, route it, learn from it One product intelligence layer does all four. It generates content grounded in real product data so answer engines have something accurate to cite, gives buyers a real experience when they land, routes each conversation to a ticket or a qualified lead, and reports back on what your content is missing. CMO · digital experience · digital marketing · Explore → ](https://www.rapidflare.ai/team/marketing)[Support ### Deflect what can be deflected, speed up what cannot A front-loaded agent on your site and inside your product answers 30-75% of common questions without a person. Behind it, a second agent with access to confidential and pre-release material drafts the answer for whatever escalates, and your engineer reviews and sends. Support leadership · technical support · customer success · Explore → ](https://www.rapidflare.ai/team/support)[AI Enablement ### The platform, the safeguards and the evidence You were asked to find the tools that improve the business, and this is the whole engineering answer: visual reasoning, grounded citations, a scalable ingestion pipeline, permissioned knowledge hubs, a practical eval framework, MCP servers, FireShield and SOC 2 Type II. Head of AI · IT and architecture · digital transformation · Explore → ](https://www.rapidflare.ai/team/ai-enablement)[Bidding ### Answer every RFQ like your best rep read it The RFQ arrives messy: the customer’s own part codes, requirements buried in notes, a deadline that ignores your backlog. Rapidflare works through the ambiguity, assembles the response from content you already approved, and flags what needs a human call, so more bids go out and none of them guess. · Explore → ](https://www.rapidflare.ai/solutions/bidding) Why one platform ## Five teams, one source of product truth The alternative is five tools that each know a bit about your products and disagree with each other. We ingest the documentation once and build every agent on top of the same layer. Ingest ### Everything technical Datasheets, catalogs, BOMs, application notes, support history, schematics, proposals and institutional knowledge, including the diagrams most systems throw away. Structure ### A product knowledge graph Normalized into a catalog and a graph of products, attributes and relationships. Created once, continually enriched. Deploy ### Where each team works Website, inside your product, partner portal, Slack, Teams, developer communities, ERP and CRM, with different knowledge scoped to each audience. Every answer is traceable to its source. Not a confidence score, a citation your engineers can open and check. Explainability as a product requirement, not a marketing claim Get started ## Pick the team with the worst bottleneck and start there Tell us which team is waiting on someone else, and we’ll build a working agent on your own product data to show you what changes. [Book a demo](https://www.rapidflare.ai/contact) [See it by industry](https://www.rapidflare.ai/by-industry) SOC 2 Type II  ·  Every answer traceable to its source --- # For bidding teams Source: https://www.rapidflare.ai/solutions/bidding > Rapidflare for bidding teams: RFQs and RFPs answered from approved content, compliance checked, with the exceptions flagged. For bidding teams # Answer every RFQ like your best rep read it The RFQ arrives messy: the customer's own part codes, requirements buried in notes, a deadline that ignores your backlog. Rapidflare works through the ambiguity, assembles the response from content you already approved, and flags what needs a human call, so more bids go out and none of them guess. [Book a demo](https://www.rapidflare.ai/contact) [All teams](https://www.rapidflare.ai/by-team) Sound familiar? ## Where bids die today ### The response depends on who picks it up Your best rep decodes the messy RFQ in minutes; everyone else forwards it, and the bid ages while it bounces. ### The answers exist, scattered Spec sheets, past responses, certificates, the compliance matrix. Assembling them by hand is the job, and it does not scale with bid volume. ### The dangerous requirement hides in the notes A compliance line on page six decides the bid, and a missed one decides it worse. What Rapidflare does here ## What Rapidflare does for a bidding team 01 ### Decodes the RFQ as it arrives Customer part codes map to your SKUs, vague references resolve against order history, and buried requirements surface as a checklist. 02 ### Assembles from approved content Responses build from spec sheets, prior approved answers, and certificates on file, every piece tagged with where it came from. 03 ### Checks compliance before you send Requirements are matched line by line, met ones cited, unmet ones flagged amber for your call rather than papered over. 04 ### Escalates the judgment calls only Pricing exceptions and cannot-meet requirements route to a person with the context attached; the other ninety percent ships. ## Bring last month's hardest RFQ and watch it drafted [Book a demo](https://www.rapidflare.ai/contact) [See the case studies →](https://www.rapidflare.ai/customers) --- # AI Enablement Source: https://www.rapidflare.ai/team/ai-enablement > Visual reasoning, grounded citations, scalable ingestion, permissioned knowledge hubs, evaluation, and FireShield safety: the engineering answer on one layer. AI Enablement # You were asked to find the tools that improve the business, and this is the whole engineering answer We look at the business process holistically and solve several use cases on one product intelligence layer, rather than handing you one more point tool to evaluate, integrate and defend. [Talk to our team](https://www.rapidflare.ai/contact)[About Rapidflare](https://www.rapidflare.ai/about) Who this is for · The AI enablement function, often inside the IT organization Your mandate · Find the tools that improve business operations, and stand behind them What we bring · A platform, not a demo, with the evaluation, safety and compliance work already done Compliance · SOC 2 Type II Accuracy and grounding ## Most enterprise AI is blind to your hardest content In semiconductors, electronics, manufacturing and infrastructure, the critical knowledge often lives inside images buried in long PDFs, not in paragraphs. Capability ### Visual Reasoning Engine Conventional retrieval flattens documents into text at ingestion and discards diagrams and structured visuals. Specifications embedded in schematics, timing charts, mechanical drawings and configuration screenshots never reach retrieval at all. We reconstruct technical visuals with layout and structural fidelity and index diagrams, tables and text in one multi-modal retrieval framework. Capability ### Grounded answers, cited Every output traceable back to the document it came from. Not a confidence score, a citation your engineers can open and check. Capability ### Block diagram generation System architecture built from a described use case, with components named from your own catalog. Capability ### Institutional knowledge The answers currently held by a handful of long-tenured engineers, captured into a system that can answer with them. Capability ### LLM-as-judge Automated quality assessment in the loop, so answer quality is measured continuously rather than sampled occasionally. Capability ### A practical evaluation framework Built to run against real traffic, not a benchmark you pass once at procurement and never revisit. In deep technical domains, diagrams are not decoration, they are the specification. When a critical detail lives in a schematic or an engineering drawing, the AI has to be able to interpret that visual directly. John Williams · Chief Scientist, Rapidflare Architecture ## What you would have to build This is the honest version of the build-versus-buy conversation. Here is the list, so you can price it properly. Infrastructure ### Ingestion that scales A pipeline built to take in hundreds of thousands of documents, datasheets, application notes, tickets, schematics, catalogs, and keep them current as they change. Architecture ### Multiple agents, multiple knowledge hubs Different agents for different audiences, each scoped to what that audience is permitted to see. The boundary is structural, not a prompt instruction. Extensibility ### MCP servers So the same product intelligence serves use cases beyond the agents we ship, including the ones your own team wants to build on top. Deployment · Web widgets, full-page, search bar, whitelabel domain, Slack, Discord, in-product and API Integration · CRM, ERP and CPQ systems, plus the knowledge sources your teams already use Compliance · SOC 2 Type II, with a trust center your security review can work from Rapidflare FireShield ## The moment it goes public, the threat model changes completely In a private dashboard, users are authenticated employees asking legitimate questions. In a public community with thousands of developers, anyone can interact with your agent, and some will try to make it say things it should not. 100% Of harmful and off-topic queries correctly handled, benchmarked against the ToxiGen academic dataset 98.5% Blocked at the first layer, before reaching the pipeline at all Zero False positives on legitimate queries Why it is layered - Some problem queries carry no explicit toxicity signal at all: they are semantically off-topic rather than overtly harmful, which makes them poor candidates for hard blocking at the input layer. - Blocking aggressively on that basis risks flagging legitimate questions that happen to touch a social topic in passing. How the second layer works - **The downstream pipeline does not need to detect toxicity.** It asks a simpler question: is this answerable from the customer’s knowledge base? - When the answer is no, the agent responds within its domain scope. - Same protection, without the false-positive cost of an overly aggressive input filter. Questions we get ## Common questions from AI and IT leaders Why should we not build this ourselves? Some of it you could. The list that is hard to sustain is: a multi-modal ingestion pipeline that preserves diagrams, a normalized product knowledge graph that stays current, permissioned hubs, an evaluation framework running against live traffic, a layered safety filter that does not destroy the false-positive rate, and the domain work of getting all of it right for electronics specifically. Most internal builds get to a working demo quickly and stall on the rest. How do you evaluate answer quality over time? With a practical evaluation framework that runs against real traffic rather than a fixed benchmark, plus LLM-as-judge in the loop. We also review conversations with customers directly, because the most useful signal is usually a specific answer that went wrong and the reason it did. Can we access the underlying intelligence, not just the agents? Yes. We expose MCP servers so your own teams can build on the same product intelligence layer, which is a common request once the first deployment proves out. How is confidential or pre-release material kept out of public answers? Multiple agents across multiple knowledge hubs, scoped by audience. Material that should not be public is not in the public agent’s hub, it is an architectural boundary rather than an instruction the model is asked to respect. What about hosting and infrastructure? Our core platform runs on Google Cloud, we benchmark models continuously and can run on other clouds. Where customers have specific infrastructure requirements we work through them directly. What does your security review look like? We are SOC 2 Type II compliant and maintain a trust center. Most enterprise reviews we go through are completed from the material there plus a call with our team. Keep reading ## Related [By Team ### Support Permissioned hubs in practice, and the two-tier support model. ](https://www.rapidflare.ai/team/support)[By Industry ### Industrial Automation What it takes to let an agent write into a live ERP order pipeline. ](https://www.rapidflare.ai/industry/industrial-automation)[By Team ### Marketing The product intelligence layer, viewed from the demand side. ](https://www.rapidflare.ai/team/marketing) Get started ## Bring us your hardest documents Send the PDFs where the answer only exists inside a diagram. That’s the fastest way to find out whether this is different from what you’ve evaluated already. [Book a demo](https://www.rapidflare.ai/contact) [Back to all teams](https://www.rapidflare.ai/by-team) SOC 2 Type II  ·  Every answer traceable to its source --- # Marketing Source: https://www.rapidflare.ai/team/marketing > One product intelligence layer gets you found, converts what arrives, routes each conversation to the right outcome, and tells you what your content is missing. Marketing # The same product intelligence that answers the question also brings people to it We normalize your catalog into a product intelligence layer. That one layer gets you found, converts what arrives, routes each conversation to the right outcome, and tells you what your content is missing. [Book a demo](https://www.rapidflare.ai/contact)[See it by industry](https://www.rapidflare.ai/by-industry) Who buys · CMO, digital experience leaders, and digital marketing, the people who own the site What they measure · Discovery, conversion, lead quality, deal velocity Runs on · Your normalized product catalog, the same layer behind every other agent Live on · Qorvo, Taoglas, Critical Link, Bay Supply The arc ## Get found, convert what arrives, route it, learn from it Four stages, one product intelligence layer underneath all of them. The order matters, because each stage depends on the one before it. Stage 01 ### Bring more people to the website Two things move here: AI visibility and search visibility. Both are downstream of having accurate, structured product content for engines to find and cite. Give us the set of prompts you need to be optimized for, and we generate the right content from the product information we already hold, grounded in your real specifications rather than written around them. This is the part most content programs get backwards. The reason a competitor gets cited is not that they wrote more; it is that what they published was structured for a machine to use. Stage 02 ### Give them a real experience when they land Deployed on your marketing site, the agent takes a customer’s high-level requirement, breaks it down and points them to the right solution. Behind a single conversation it may call ten different tools, working against a normalized product catalog, which is why the recommendation comes back accurate rather than merely plausible. We have done this repeatedly across customers, and it produces both a good experience and real conversion. Deal velocity improves too, because the buyer arrives at your sales team already narrowed down. Stage 03 ### Route the conversation to an outcome Dynamic routing decides what each conversation becomes. It can escalate as a customer success ticket, or create a lead with the customer’s intent clearly identified. That second one is the difference between a form fill and a qualified opportunity. The lead arrives with the requirement already articulated: what they are building, what they need, and what the agent recommended. Stage 04 ### Learn from all of it The analytics dashboard is extremely customizable, and it surfaces product gaps and content gaps based on what people asked. We use it to continuously improve the platform, and you use it to decide what to write next. The site gets better every month instead of decaying between redesigns. The foundation ## Why it all runs on one layer Content, on-site experience and lead quality are usually three separate vendors that know nothing about your products. Here they are three outputs of the same thing. Ingest ### Your technical documentation Datasheets, catalogs, application notes, support history and schematics, including the diagrams most systems discard at ingestion. Normalize ### Into a product catalog Structured, queryable and consistent across product families, which is what makes an accurate recommendation possible. Serve ### Content, conversation and routing The same layer generates the content that gets you found, powers the conversation that converts, and classifies the intent that routes. Live on customer sites · Qorvo · · Taoglas · · Critical Link · · Bay Supply Taoglas runs a public AI product recommendation experience. Qorvo runs the agent on their main site. Critical Link runs it in the site search bar. Bay Supply runs a full selection-to-quote experience on their storefront. Questions we get ## Common questions from marketing leaders Is this a chatbot? No, and the difference is worth being precise about. A chatbot retrieves from a help center. This reasons over a normalized product catalog, calls tools during a single conversation, and returns a recommendation with the reasoning shown. The output is a decision, not a link. How does the content generation work? You tell us the prompts and queries you want to be found for. We generate content grounded in the product information we already hold, real specifications, real part data, rather than writing around the topic. That is what gives an answer engine something worth citing. What does the lead look like? It arrives with the intent identified: what the buyer described, what was clarified, and what was recommended. Your sales team opens it already knowing the application, which is the difference between a form fill and a qualified opportunity. Who owns this internally, marketing or IT? Marketing owns the outcome and usually buys it. IT is generally involved on deployment and data access, and on manufacturer sites they are sometimes the buyer instead. Both paths are normal. What happens to the analytics we get back? It is yours to act on and we work through it with you. Document gaps become a content backlog, and query themes tell you what your buyers are trying to do, which is usually more useful than any keyword report. Keep reading ## Related [By Industry ### B2B e-Commerce When the conversation should end in a quote rather than a lead. ](https://www.rapidflare.ai/industry/b2b-ecommerce)[By Industry ### Manufacturers Product discovery on a manufacturer’s site, and the long-tail customer. ](https://www.rapidflare.ai/industry/manufacturers)[By Team ### Support Where the escalated conversations go. ](https://www.rapidflare.ai/team/support) Get started ## Start with your product pages We’ll ingest your public documentation, put a selection agent on a section of your site, and show you what visitors ask when they can finally ask properly. [Book a demo](https://www.rapidflare.ai/contact) [Back to all teams](https://www.rapidflare.ai/by-team) SOC 2 Type II  ·  Every answer traceable to its source --- # Sales Source: https://www.rapidflare.ai/team/sales > Field sales, application engineers, sales engineers, FAEs, and channel account managers, working from the same product knowledge in the tools they already use. Sales # Stop being the person who collects the question and takes it back to the factory Field sales, application engineers, sales engineers, FAEs, and channel account managers, working from the same product knowledge in the tools they already use. [Book a demo](https://www.rapidflare.ai/contact)[See it by industry](https://www.rapidflare.ai/by-industry) Animated illustration: three chapters of a sales team with Rapidflare. On a live visit a customer asks whether the R-441M holds 4-20 mA accuracy from -40°C to 85°C. Without Rapidflare the answer takes six days and the customer goes quiet; with Rapidflare a cited answer lands in nine seconds and a proposal is requested on the call. Then the call notes become a technical proposal sent 41 minutes later, and a rep three days into the job answers a functional safety question with a cited source. Answer in the room, propose the same hour, ramp in days. Who buys · VP of Sales, or a CRO where one exists Who uses it · Field sales · application engineers · sales engineers · FAEs · channel account managers Where · Slack, in the flow of work, and directly in the Rapidflare dashboard Headline value · Fast ramp-up, and direct answers to the customer The core problem ## The customer is not waiting on an answer, but on your org chart Every question a rep cannot answer starts an internal relay, and the relay is the delay. What happens today - A rep hits a question they cannot answer, which happens constantly with a technical catalog. - They go back into the company and work through application engineers, product managers and architects. - Those people are the same bottleneck for every deal in the pipeline, so the queue is real. - Days pass. The rep chases. The customer, meanwhile, is talking to someone else. - In the meeting itself, the rep collects the question and goes back to the factory, which is exactly how they come across. What changes - **The rep answers it themselves.** Directly, without routing through anyone. - **In front of the customer, they look it up and answer on the spot,** rather than taking notes and promising to follow up. - They present as someone who knows the product, not someone who fetches information about it. - Your application engineers get their week back for the work only they can do. Two headline values ## Ramp fast, answer directly Everything else on this page follows from these two. Value 01 ### A new rep gets productive quickly Ramp-up speed is the real constraint on any plan to grow a sales team or add channel partners. It is why headcount plans slip and why new territories take a year to produce. With the product knowledge available on demand, new reps and new partners get up to speed very quickly and walk into customer conversations feeling confident, instead of spending months learning a catalog before they are useful. This applies as much to channel partners as employees. In a channel-led business, partner ramp is your ramp. [Book a demo](https://www.rapidflare.ai/contact) Value 02 ### Response time to the customer The rep answers the technical question themselves, at the moment it is asked. No internal relay, no queue behind the application engineering team, no "let me find out and come back to you." Response time is the metric most sales leaders can feel immediately, and it is the one that moves first. [Book a demo](https://www.rapidflare.ai/contact) What else it does ## Better questions in the room, better documents after it Enablement is not only about answering, it is about knowing what to ask, and being able to produce the right technical material afterwards. In the meeting ### Ask the right questions The agent helps reps ask the questions that truly narrow a requirement, which changes both the size of the deal and how fast it moves. After the meeting ### Craft strong RFP responses Well-structured responses built quickly, from your own documentation rather than a boilerplate template. In the deal ### Provide the right technical solution Technical proposals with a real solution behind them, assembled for that customer, which is most of what a good proposal really is. In Slack · Ask in the channel where the deal is already being discussed, and get a cited answer back in seconds In the dashboard · Log in directly for longer research, comparisons and proposal work Everywhere · Every answer traceable to the document it came from, so a rep can send the source with the reply Outcomes ## What the VP of Sales sees Leading indicators - Time to respond to a customer’s technical question - Number of questions escalated to application engineering - Time for a new rep or partner to first qualified opportunity - Proposal and RFP turnaround Lagging indicators - **Deal size,** from asking the right questions early - **Sales velocity,** from removing round trips - **Ramp time,** and therefore the cost of every hire - **Channel productivity,** where partners sell your line as confidently as your own team Every technical question a rep can answer themselves is a round trip removed from the deal, and a week returned to your application engineers. Questions we get ## Common questions from sales leaders Will my reps use it? It lives in Slack, which is where they already are. The two things reps adopt without a mandate are things that make them look good in front of a customer and things that stop them chasing colleagues, and this is both. What stops it giving a rep a confidently wrong answer? Every answer carries a citation back to the source document, so a rep can check it and send it. Beyond that we run continuous evaluation against real traffic, and where the agent does not have grounds to answer, it says so rather than filling the gap. Can channel partners have it too? Yes, usually through a partner portal deployment scoped to what partners should see. In a channel-led business this is often the higher-value half of the rollout. Does this replace our sales enablement platform? It answers a different question. Enablement platforms manage and distribute content; this reasons over your technical documentation to answer a specific customer’s specific question. Most customers run both. How quickly will we see ramp time move? Faster than you would expect, because the mechanism is immediate: a new rep stops being blocked on the day they get access. What takes longer is expanding coverage across every product line, which we do progressively. Keep reading ## Related [By Industry ### Distributors Where no rep can know every vendor line, and ramp is the constraint. ](https://www.rapidflare.ai/industry/distributors)[By Industry ### Physical Security Channel-led selling, and enabling partners as well as your own team. ](https://www.rapidflare.ai/industry/physical-security)[By Team ### Support What happens to the questions that do need to escalate. ](https://www.rapidflare.ai/team/support) Get started ## Put it in one Slack channel Pick a product line, give us the documentation, and let one sales team use it for two weeks. That’s usually the whole evaluation. [Book a demo](https://www.rapidflare.ai/contact) [Back to all teams](https://www.rapidflare.ai/by-team) SOC 2 Type II  ·  Every answer traceable to its source --- # Support Source: https://www.rapidflare.ai/team/support > Two-tier AI support: a front-loaded agent that answers before a ticket exists, and an internal agent that drafts from confidential material for escalations. Support # Answer it before it becomes a ticket, then make every ticket that survives faster Multiple agents across multiple knowledge hubs is a core capability of the platform, and it is what lets the customer-facing agent and the internal one draw on very different knowledge, safely. [Book a demo](https://www.rapidflare.ai/contact)[See it by industry](https://www.rapidflare.ai/by-industry) Who buys · Support leadership, or a CRO where support sits alongside sales and marketing Deflection · 30-75% of commonly asked questions, depending on use case and complexity Where · Website · inside your product · partner portal · Slack and Teams · developer communities Deployed with · AMD ROCm, Brivo, Eagle Eye Networks, Tolomatic Two tiers ## One platform, two very different knowledge boundaries The public agent and the internal agent are not the same agent with different permissions. They are different hubs, which is what makes the boundary safe. Tier 1 · External ### The front-loaded agent Deployed on your website and inside your product, answering technical support questions before they reach a person. It is the first responder to everything. It handles 30% of commonly asked questions end to end in a straightforward deployment, and up to 75% depending on the use case and the complexity of your products. Every customer is different, and we would rather give you the range than a single flattering number. In the AMD ROCm developer community (Discord and Discourse, thousands of developers, public) it reduced L1 support requests by more than 30%. Tier 2 · Internal ### The agent behind the escalation When a ticket escalates to your internal technical support team, those people can see things the public agent cannot: confidential data, and products not yet released to market. Their knowledge hub reflects that. A support ticket or email arrives. We intercept it and produce the right answer from the information that team is entitled to see. The engineer reviews it, reads it, and sends it back to the customer, very quickly. Human judgment stays in the loop. The agent does the retrieval and the drafting; your engineer approves and sends. Why the architecture matters ## An unreleased product should never surface on your website Scoping by hub rather than by instruction is the difference between a policy and a guarantee. Hub 01 ### Public Published documentation only. What a customer or an anonymous visitor is entitled to see, and nothing more. Hub 02 ### Partner Channel-appropriate depth for dealers and integrators, more than the public hub, less than internal. Hub 03 ### Internal Confidential material, support history, and products not yet released. Available to your engineers, invisible everywhere else. The question every support leader asks in the second demo is "what stops it telling a customer about a product we have not launched?" The answer is that the material is not in that agent’s hub at all. Beyond deflection ## It also tells you what your documentation is missing Alongside the agent we hand back analytics on document gaps and on the conversations happening, then work with you to close them. What you get back - **Document gaps,** the questions being asked that your content cannot answer. - **Conversation themes,** what customers and partners are trying to do on your platform. - **Answer quality review,** including the conversations that went badly and why. Why it compounds - **Deflection is not a fixed ceiling.** It is a function of coverage, and coverage is something you can improve deliberately. - **Your knowledge base improves as a by-product** of running the agent, which helps your human team too. - **Next quarter’s number should be higher than this quarter’s,** and you will know exactly why. 30-75% Of commonly asked questions handled without a person, depending on use case and complexity 30%+ Reduction in L1 support requests in the AMD ROCm developer community Minutes Rather than hours, for the questions that do reach a human Questions we get ## Common questions from support leaders Why is the deflection number a range? Because it truly is one. It depends on how complex your products are, how good your documentation is today, and which surface you deploy on. 30% is what a straightforward deployment achieves; up to 75% is achievable where the question mix and the content support it. We would rather set that expectation than quote you the top of the range. What happens to the tickets it cannot answer? They escalate to your team, but not empty-handed. The internal agent drafts the answer from confidential and pre-release material your engineers can see, and the engineer reviews and sends. The escalation still happens; it just takes minutes instead of hours. Can it live inside our product rather than on a help center? Yes, and that is where it performs best. Embedded in your product it becomes the first thing a customer meets when they hit a problem. Several of our physical security customers run it this way. How do you handle a public developer community? Carefully: the threat model there is completely different from an authenticated dashboard. Our FireShield safety layer handled 100% of harmful and off-topic queries in benchmarking against the ToxiGen dataset, with 98.5% blocked at the first layer and no false positives on legitimate questions. How do we get comfortable before it goes live? Shadow mode. The agent answers real incoming questions without exposing anything, your team reviews and ranks the responses, and you go live when the quality is where you want it. AMD ran two weeks of shadow production testing on Discord and forum questions before launch. Keep reading ## Related [By Industry ### Physical Security Embedded in the product, in the partner portal, and in Slack. ](https://www.rapidflare.ai/industry/physical-security)[By Team ### AI Enablement The safety layer, the evaluation framework and the permission model. ](https://www.rapidflare.ai/team/ai-enablement)[By Industry ### Manufacturers Developer communities and the ROCm deployment. ](https://www.rapidflare.ai/industry/manufacturers) Get started ## Run it in shadow mode first Point it at your real incoming questions without exposing anything. Review the answers with your team, then decide. [Book a demo](https://www.rapidflare.ai/contact) [Back to all teams](https://www.rapidflare.ai/by-team) SOC 2 Type II  ·  Every answer traceable to its source --- # Customers Source: https://www.rapidflare.ai/customers > The companies that trust Rapidflare with their catalogs: OEMs, distributors, and integrators in the electronics industry, with the numbers attached. Customers # Trusted where the product is the hard part OEMs, component makers, distributors, and integrators in the electronics industry run Rapidflare on their real catalogs: thousands of SKUs, dense datasheets, and customers who ask hard questions. [Read the case studies](https://www.rapidflare.ai/customers/casestudies) [Become one of them](https://www.rapidflare.ai/contact) The companies ## Live with the names your customers already buy from ![AMD](https://www.rapidflare.ai/logos/amd.png) ![Qorvo](https://www.rapidflare.ai/logos/qorvo.png) ![Taoglas](https://www.rapidflare.ai/logos/taoglas.png) ![Amphenol](https://www.rapidflare.ai/logos/amphenol.png) ![Brivo](https://www.rapidflare.ai/logos/brivo.png) ![Eagle Eye Networks](https://www.rapidflare.ai/logos/eagle-eye.png) ![Macnica](https://www.rapidflare.ai/logos/macnica.png) ![Swift Sensors](https://www.rapidflare.ai/logos/swift-sensors.png) ![Portal.io](https://www.rapidflare.ai/logos/portal.png) ![Critical Link](https://www.rapidflare.ai/logos/critical-link.png) ![Sage Integration](https://www.rapidflare.ai/logos/sage.png) ![Alibi Security](https://www.rapidflare.ai/logos/alibi.png) ![Tolomatic](https://www.rapidflare.ai/logos/tolomatic.png) ![Actuate](https://www.rapidflare.ai/logos/actuate.png) ![DeepX](https://www.rapidflare.ai/logos/deepx.svg) ![McFadyen Digital](https://www.rapidflare.ai/logos/mcfadyen.png) ![Rolling Wireless](https://www.rapidflare.ai/logos/rolling-wireless.png) ![Security Industry Association](https://www.rapidflare.ai/logos/sia.png) The numbers ## Measured in their deployments, not our slides 99,323 · Product questions answered on Alibi Security's website 30%+ · Fewer L1 support requests in the AMD ROCm developer community 80% · Of purchase order entry automated at Tolomatic 8x · More positive feedback after AI joined SIA's site search In their words ## What the operators say > “Rapidflare's AI agents consistently exceed the accuracy requirements we thought possible. They decode complex specifications and present them in simple, usable answers.” > “We sought the assistance of Rapidflare to be a real partner in our agentic AI journey, one that listens to our feedback and structures AI to meet our members’ needs.” > “The level of engagement and responsiveness from the team stood out. They collaborated with us to implement additional features that enhanced the solution beyond the original scope.” Where they come from ## Six industries, one shape of problem [Manufacturers →](https://www.rapidflare.ai/industry/manufacturers)[Distributors →](https://www.rapidflare.ai/industry/distributors)[System integrators →](https://www.rapidflare.ai/industry/system-integrators)[Physical security →](https://www.rapidflare.ai/industry/physical-security)[Industrial automation →](https://www.rapidflare.ai/industry/industrial-automation)[B2B e-commerce →](https://www.rapidflare.ai/industry/b2b-ecommerce) The proof, in depth ## Three stories with the receipts attached [ 30% · Fewer Level 1 support queries Global access-control leader ### An access-control leader cut Level 1 support queries by 30% One agent grounded in a cleaned-up knowledge base now answers support teams, SaaS users, and resellers, powering 10,000 conversations a month. - Physical security and access control - Technical support - Sales - OEM ](https://www.rapidflare.ai/customers/access-control)[ 99,000+ · Authorized dealer and integrator product questions supported Cloud-managed video surveillance provider ### How a cloud-managed video surveillance solution provider made its product expertise instantly accessible across its dealer and integrator channel Authorized security dealers and integrators ask technical questions in natural language and get answers grounded in the company's own product knowledge. - Physical security and access control - Technical support - Sales - OEM ](https://www.rapidflare.ai/customers/alibi)[ 9,000+ · AI-assisted interactions in the first seven months Security Industry Association ### How SIA scaled access to trusted industry knowledge with askSIA The security industry's standards authority turned its reference library into a site-wide AI answer layer, without giving up the rigor its members rely on. - Physical security and access control - Marketing ](https://www.rapidflare.ai/customers/sia) [Browse the full case study library →](https://www.rapidflare.ai/customers/casestudies) ## Looking for pricing, a benchmark, or a customer reference? [Get in touch](https://www.rapidflare.ai/contact) [See how deployment works →](https://www.rapidflare.ai/product/deployment) --- # An access-control leader cut Level 1 support queries by 30% Source: https://www.rapidflare.ai/customers/access-control > One agent grounded in a cleaned-up knowledge base now answers support teams, SaaS users, and resellers, powering 10,000 conversations a month. The problem ## Global scale, a broad portfolio, and a flood of Level 1 requests A global leader in cloud-based access control and smart building solutions was feeling the strain of its own growth. A broad portfolio spanning access control, video, mobile credentials, smart home integrations, and third-party applications meant support agents combed extensive technical documentation for complex cases while a flood of repetitive Level 1 requests, login resets, basic configuration, competed for the same hours. For enterprise and property management customers, every delay in access control carries real cost: downtime, risk, and frustrated occupants. The approach ## Make the documentation AI-ready first, then deploy outward The work started with the knowledge, not the bot. The company's technical content was locked in large, fragmented documentation spread across systems, hard for people to search and nearly impossible for AI to interpret consistently. Rapidflare and the customer ran a content-first program to make it AI-ready, then piloted the agent with a small group of support engineers before expanding it outward: into Slack, into the SaaS application itself, and finally onto the partner portal. The outcome ## A third fewer Level 1 tickets, across three surfaces Level 1 support queries fell by 30%, freeing agents for the complex cases. SaaS users resolve entry-level issues in the product, in the moment, which shows up in satisfaction and retention. Resellers on the partner portal get immediate, accurate product knowledge, lifting sales effectiveness and revenue. Together the deployments now power more than 10,000 conversations every month. 10,000+ · Conversations powered each month 3 · Surfaces: Slack, the SaaS application, and the partner portal ## Making the documentation AI-ready first The real blocker was never the model. It was that accurate answers were scattered through large, overlapping, sometimes conflicting documents. Before any agent went live, Rapidflare and the customer: - Mapped and consolidated content into a single system of record - De-duplicated and cleaned the data, removing outdated and conflicting entries - Classified material as internal or external, so access stays secure and relevant - Closed knowledge gaps surfaced by real AI query outcomes, resolving ambiguities the documents had carried for years That structured foundation is what lets one agent answer consistently across very different audiences, from a support engineer mid-ticket to a reseller mid-deal. ## From pilot to partner portal Adoption followed the same discipline. A small group of support agents piloted the assistant inside their daily workflow and became its first advocates. From there the agent moved to Slack for the wider team, then into the SaaS application where end users self-serve entry-level issues, and finally onto the partner portal, where resellers ask product questions in the flow of selling. Each surface runs on the same knowledge base, with access scoped to the audience. ## See it run on your own catalog [Book a demo](https://www.rapidflare.ai/contact) [Back to the library →](https://www.rapidflare.ai/customers/casestudies) --- # How a cloud-managed video surveillance solution provider made its product expertise instantly accessible across its dealer and integrator channel Source: https://www.rapidflare.ai/customers/alibi > Authorized security dealers and integrators ask technical questions in natural language and get answers grounded in the company's own product knowledge. The problem ## Every unanswered product question can slow down a sale or support interaction A dealer or integrator might need to know which product to recommend, whether a camera works with a recorder, which model meets a spec, or the closest replacement for a competitive part. The information usually exists, spread across product pages, datasheets, compatibility tables, and application notes. Finding it is only part of the problem; the harder part is connecting the right pieces into guidance for the specific question being asked. When a partner cannot do that confidently, the question moves upstream to a sales or support engineer, and multiplied across a large channel, that consumes substantial expert time while the dealer or integrator waits. The approach ## Give the channel direct access to product expertise, not just product search The company deployed Rapidflare as a product intelligence layer across its product knowledge. Rather than retrieving a page or a document with matching keywords, Rapidflare reasons across environmental specifications, camera capabilities, recorder compatibility, accessory requirements, and configuration guidance together, then answers the actual question a dealer or integrator is trying to solve. The partner starts with the problem; Rapidflare does the work of finding, connecting, and interpreting the relevant product information. The outcome ## More than 99,000 channel product questions supported The deployment has supported more than 99,000 authorized dealer and integrator product conversations, the everyday questions that come up while selling, specifying, installing, and supporting the company's products. Sales and support engineers no longer need to be the first stop for every question whose answer already exists in the company's product knowledge; their time goes to the questions that need specialist judgment. Product expertise on demand · Answers reasoned across specifications, compatibility, application guidance, and cross-reference data Fewer routine escalations · Channel partners get answers directly instead of depending on an engineer for every product question ## From searching for information to getting guidance The old workflow was a chain of separate lookups: find the page, read the datasheet, interpret the spec, check the compatibility table, research the competitor, then ask an engineer if still unsure. Every one of those steps collapses into a single question asked directly to Rapidflare’s agent on the company’s site. Traditional channel workflow Search for the right product page or document Read multiple datasheets Interpret specifications manually Search compatibility tables Research competitive products separately Ask a sales or support engineer when uncertain Wait for an expert before moving forward Ask Rapidflare “Which camera works with this recorder, and is it rated for this environment?” One question, in natural language, on the company's own site One grounded answer · Reasoned across specs, compatibility, application guidance, and cross-reference data, sourced to the company's own documentation. Selection · Compatibility · Cross-reference ## Reduce repetitive question load on technical teams Many questions reaching sales and support engineers matter to the person asking, but are not novel to the company. The answer already exists across specifications, datasheets, compatibility documentation, installation guidance, application notes, and competitive cross-reference data. Rapidflare turns that existing knowledge into an answer layer the channel can use directly. - Rapidflare handles repeatable product questions - Experts focus on the questions that need an expert ## Product intelligence, not another search box Traditional search helps someone find information. Rapidflare is designed to help someone use that information to answer a question. A dealer or integrator should not need to know which document contains the answer, which product family uses different terminology, or which compatibility table to check. They describe what they are trying to accomplish, and Rapidflare reasons across the relevant product knowledge to return grounded guidance for that requirement. ## Supporting the people who represent the product to the customer The company is a cloud-managed video surveillance solution provider, and much of its product experience happens outside its own organization. Authorized dealers and integrators select products, compare options, validate requirements, design systems, and resolve product questions on the company’s behalf. Rapidflare extends the company’s product expertise into that channel without requiring the internal engineering team to participate in every interaction. ## Built for technical questions where accuracy matters Making product expertise scalable only works if the answers stay grounded in authoritative product information. Rapidflare reasons across the company’s own specifications, technical documentation, compatibility information, application guidance, and cross-reference data, rather than depending on generic model knowledge alone. ## What this deployment demonstrates - Product expertise can scale across the channel: dealers and integrators get technical guidance without one-to-one involvement from an internal expert on every question - Answers can go beyond document retrieval: Rapidflare reasons across multiple sources of product knowledge to resolve the specific requirement behind the question - Technical teams can focus on higher-value work: repeatable product questions are handled from existing knowledge, leaving engineers available for complex situations - Channel partners can move faster: partners get guidance the moment a question occurs, instead of waiting on an answer to progress a quote or install ## See it run on your own catalog [Book a demo](https://www.rapidflare.ai/contact) [Back to the library →](https://www.rapidflare.ai/customers/casestudies) --- # Case study library Source: https://www.rapidflare.ai/customers/casestudies > Proof, not adjectives. Real results from teams in the electronics industry, tagged so you can find the one that looks like you. Case study library # Proof, not adjectives Real results from teams in the electronics industry. Every story is tagged by industry, team, and buyer type, so the one that looks like your business is easy to find. ## Looking for pricing, a benchmark, or a customer reference? [Get in touch](https://www.rapidflare.ai/contact) [See how deployment works →](https://www.rapidflare.ai/product/deployment) --- # DEEPX put its SDK, repositories, and engineering docs behind one answer layer Source: https://www.rapidflare.ai/customers/deepx > The NPU maker unified DXNN SDK documentation, GitHub repositories, and internal engineering systems into one cited answer layer for edge AI developers. The problem ## The knowledge existed, it was just spread across four kinds of system Deploying AI silicon is not one question, it is a chain of them: which model format the toolchain accepts, how to quantize for the target, what the SDK expects, why a build fails on one board and not another. DEEPX had answers to all of it. They were spread across GitHub repositories, DXNN SDK documentation, developer portals, tutorials, and internal support knowledge. An engineer mid integration had to know which of those systems held the answer before they could start looking. As the DEEPX ecosystem grew across robotics, smart mobility, industrial automation, and intelligent infrastructure, that lookup cost grew with every new developer. The approach ## One intelligence layer over the whole developer surface Rapidflare ingested the technical parameters of the products themselves, schematics, configuration guides, and maintenance logs, alongside the SDK documentation and the repositories. The platform reasons over the hardware and the software together rather than treating each document as a separate lookup, using knowledge graphs, structured reasoning with tool calling, and source level traceability. Every answer carries a deep link to the document it came from, which is the part that matters in mission critical work: an engineer can check the claim rather than trust it. The outcome ## Live across support, engineering, and developer enablement The platform is live and integrated across three DEEPX systems: technical support, engineering, and developer enablement. Developers, customers, and DEEPX's own engineers get instant answers cited across what used to be separate knowledge sources. Before rolling it out, DEEPX benchmarked Rapidflare's accuracy internally against the layered questions that come with deploying new AI silicon at scale. The roadmap runs toward the edge itself: automated troubleshooting, self diagnosis, and configuration guidance on factory robots and autonomous machinery. 4 source types · GitHub repositories, DXNN SDK documentation, developer resources, and internal engineering systems DX-M1, DX-M2 · NPU families the knowledge layer has to answer for Deep links · Every answer cited back to the source document ## Why silicon makes this harder A camera or a sensor has a spec sheet. An NPU has a spec sheet, a toolchain, a runtime, a set of supported model formats, quantization behavior that varies by target, and a board bring-up path. The question “will this work” decomposes into a dozen smaller ones, and the answers sit at different altitudes: some in silicon documentation, some in SDK reference, some in a repository issue thread. That is the shape of the problem Rapidflare was built for, and it is why DEEPX tested accuracy before scale. ## The citation is the product DEEPX’s own framing is that trust is the constraint, not capability. An answer an engineer cannot verify is worse than no answer, because it costs them the time to discover it was wrong. Every response the layer returns is cited with a deep link into the source, so verification takes one click. > Physical AI systems will increasingly depend on trusted knowledge as much as they depend on compute. Our work with DEEPX demonstrates how organizations can create a reliable intelligence layer. > > Prush Palanichamy, Co-Founder and CRO, Rapidflare ## Where it goes next Both companies are working toward closing the loop between documentation and what happens in the field, so operational feedback from deployed systems feeds back into the knowledge layer. The end state is edge devices, factory robots and autonomous machinery, running automated troubleshooting and self diagnosis locally. ## See it run on your own catalog [Book a demo](https://www.rapidflare.ai/contact) [Back to the library →](https://www.rapidflare.ai/customers/casestudies) --- # How SIA scaled access to trusted industry knowledge with askSIA Source: https://www.rapidflare.ai/customers/sia > The security industry's standards authority turned its reference library into a site-wide AI answer layer, without giving up the rigor its members rely on. The problem ## Deep, authoritative content, and a long walk from intent to insight SIA's website already held a deep, authoritative body of knowledge: standards, training and certifications, research reports, and industry events. The problem was never content quality. It was the distance between intent and insight. Manufacturers, integrators, consultants, and enterprise security leaders each arrive with different questions and different levels of familiarity, and finding the precise answer took time and a working knowledge of how the site was organized. First-time and non-member visitors often did not know where to begin. The approach ## A homepage beta grew into the site-wide answer layer SIA and Rapidflare launched askSIA as a beta widget on the homepage, answering natural-language questions against SIA's own resources. Real queries drove the next two moves: askSIA's intelligence was merged into the site's native search, adding an AI overview and intent understanding on top of the results people already trusted, and then became the site-wide entry point in the primary hero banner. When event queries exposed a weakness every general model shares, surfacing outdated listings, Rapidflare shipped a chronology-aware handling layer within two months. The outcome ## Faster answers for members, and a signal SIA never had before askSIA has handled more than 9,000 AI-assisted interactions in seven months, engagement has grown roughly five-fold since early deployment, and positive user feedback rose eight-fold once AI augmented native search. Just as valuable: aggregated query patterns now show SIA where members struggle and what content is missing, driving an AI-first restructuring of high-value sections like the reports library. 469 · Queries handled in the first month of beta 8x · More positive feedback after AI joined native search ~5x · Growth in engagement from early deployment Seconds · Time to information, down from minutes ## Stage one: the beta that proved demand askSIA began as a homepage widget inviting visitors to ask questions in plain language. It handled 469 queries in its first month, early proof that the demand was real. SIA and Rapidflare reviewed responses together through this phase to keep every answer aligned with SIA’s authoritative content. One limitation surfaced early: time-sensitive questions. Like every large language model, the initial system struggled to prioritize upcoming events over past ones. Rapidflare built a chronology-aware handling layer for event queries within two months. Later benchmarking showed leading general-purpose models, including ChatGPT’s flagship release, still failing this class of question: domain-specific system design beats raw model capability. ## Stage two: intelligence inside native search Rather than replacing the search members already used, askSIA joined it. Every search now returns an AI-generated overview alongside the traditional results, with intent and context understood where keywords alone fall short. Standards, trainings, reports, and events surface even for ambiguous questions. Positive user feedback rose eight-fold after the change. ## Stage three: site-wide, and a signal source askSIA now sits in the primary hero banner as the default way into SIA’s knowledge. And at scale it runs in both directions: a discovery layer for members, and a continuous signal for SIA. Aggregated query data shows where intent goes unmet, which content is redundant, and what to write next, feeding an AI-first content strategy and concrete restructuring of sections like the reports library. > AskSIA has become my go-to for quickly getting to the information I need. > > Byron Haugaboo ## What’s next SIA and Rapidflare are deepening intent understanding, refining response precision, and extending AI-assisted discovery across more content areas, so SIA’s knowledge stays structured, discoverable, and authoritative for both human and AI-driven search. ## See it run on your own catalog [Book a demo](https://www.rapidflare.ai/contact) [Back to the library →](https://www.rapidflare.ai/customers/casestudies) --- # Benchmark methodology Source: https://www.rapidflare.ai/methodology > What we can say today about the 95% extraction accuracy benchmark, and what we have not published yet. Methodology # How we measured extraction accuracy The full write-up is not published yet. This page is a placeholder. We quote Rapidflare at 95%, Contextual AI at 62%, and AWS Textract at 49% on extraction accuracy. A claim like that only means something if you can see how it was measured, so here is where we are: the definition and the scoring rule are settled, the published detail is not. ## What we measured Extraction accuracy: whether the engine reads a value out of a real technical document correctly, including tables, multi-column layouts, and values that span a drawing and its notes. ## How we scored it Each extracted value is checked against a human-verified ground truth. A value counts as correct only when it matches the source exactly, unit included. Partial reads do not count. ## Still to publish We have not yet published the document set (its size and where the documents came from), the dates the runs were made, or the versions and settings used for each tool in the comparison. Until those are here, treat the three numbers as our own reported figures, not as an audited result. ## Want the detail sooner? Ask us and we will walk you through the run. Better still, bring a document of your own that usually breaks AI, and we will show you what the engine does with it. [Get in touch](https://www.rapidflare.ai/contact). [Back to the Platform](https://www.rapidflare.ai/product/platform) --- # AI Readiness Report Source: https://www.rapidflare.ai/resources/ai-readiness-report > Get a free assessment of how AI-ready your product documentation is, with specific findings and recommendations for improving it. Complimentary AI Readiness Report # How AI-ready is your product knowledge? Find out where your existing product documentation helps, or limits, the AI systems that depend on it. You’ll get a practical assessment of your product knowledge, including specific findings, priority areas, and clear recommendations for improving AI readiness. What we assess ## Four dimensions of AI readiness Your product knowledge is assessed across four areas that directly affect how reliably AI can use it. 01 ### Retrievability Can AI consistently find the right information when it needs to answer a question? 02 ### Interpretability Is the information clear enough for AI to understand without relying on unstated assumptions or human context? 03 ### Consistency Do different documents, systems, or versions contain conflicting or inconsistent information? 04 ### Completeness Is enough context available for AI to reach an accurate and useful answer? You’ll receive an actionable insight into what does or does not make your content AI ready. See what you’ll get ## A practical view of where your product knowledge stands Your report will highlight what is working, where AI may struggle, and what is worth improving first. Sample report | Illustrative only AI Readiness Overview Overall AI Readiness · 68/100 Retrievability · Strong Interpretability · Moderate Consistency · Needs attention Completeness · Moderate Priority findings 1. 1 · **Conflicting specifications across product documents**The same product attribute appears differently across multiple sources, increasing the likelihood of inconsistent AI responses. 2. 2 · **Key product relationships are implicit**Experienced users may know which products, accessories, or configurations work together, but those relationships are not explicitly documented. 3. 3 · **Important information is difficult to retrieve**Relevant details are buried within long PDFs and tables without enough surrounding structure to make them consistently discoverable. Example shown for illustration. Your assessment will be based on your own product knowledge. One customer, in their words “By turning complex roadmaps, technical documentation, Salesforce inquiries, and Jira data into clear, actionable answers, Rapidflare helps our teams work more efficiently, support customers better, and avoid solving the same problem twice.” ![Rolling Wireless](https://www.rapidflare.ai/logos/rolling-wireless.png) **Inigo Leturia**Director, System Engineering & Customer Success Get started ## See how AI-ready your product knowledge is Get a clearer picture of what AI can reliably use today, where problems may arise, and what to improve first. - You don’t need to be a Rapidflare customer - You don’t need an AI system already deployed [Start my free assessment](#ar-form) Free  ·  No obligation --- # Calculators Source: https://www.rapidflare.ai/resources/calculators > Put your own numbers in: how many expert hours documented questions are absorbing, and what answering them automatically returns. Calculators # Your numbers, not our claims Most technical questions are answered by an expert reading documentation someone else could have read. Put your own numbers in and see what that habit costs, and what answering the documented share automatically returns. Expert time calculator ## What the documented questions are costing you Technical questions per month Minutes to answer one today Share answerable from documentation Loaded cost per expert hour · expert hours returned per month · per year, at your loaded cost Arithmetic on your inputs, nothing else. What share of your questions is answerable from documentation is the number worth pressure-testing, and a pilot on your own catalog measures it for real. ## Looking for pricing, a benchmark, or a customer reference? [Get in touch](https://www.rapidflare.ai/contact) --- # Events Source: https://www.rapidflare.ai/resources/events > Where to meet Rapidflare: upcoming industry shows, summits, and conferences across physical security, semiconductor, and AI. Events # Meet us at an upcoming event Trade shows, summits, and conferences where you will find Rapidflare on the road this quarter. Ask us where we will be next, or get us to your event. ![The Rapidflare team at the Ai4 2026 booth in Las Vegas](https://www.rapidflare.ai/events/ai4-group.jpeg) ![Rapidflare with the Macnica team at Automate in Chicago](https://www.rapidflare.ai/events/automate-macnica.jpeg) ![The Rapidflare team at the ISC Startups booth](https://www.rapidflare.ai/events/isc-startups-booth.jpeg) ![Rapidflare and DEEPX at their partner booth](https://www.rapidflare.ai/events/deepx-booth.jpeg) ![Rapidflare at the CES 2026 sign](https://www.rapidflare.ai/events/ces-2026-sign.jpeg) ![Rapidflare with the Tolomatic team at their booth](https://www.rapidflare.ai/events/tolomatic-booth.jpeg) ![Rapidflare at the AMD booth](https://www.rapidflare.ai/events/amd-booth.jpeg) ![Rapidflare and DEEPX ecosystem partners](https://www.rapidflare.ai/events/deepx-partners.jpeg) ![The Rapidflare team at the ISC Startups Security reception](https://www.rapidflare.ai/events/isc-startups-security.jpeg) ![A Rapidflare live product demo at the Ai4 booth](https://www.rapidflare.ai/events/ai4-booth-demo.jpeg) ![Rapidflare at CES 2026](https://www.rapidflare.ai/events/ces-2026-mammotion.jpeg) ![The Rapidflare team at Plug and Play](https://www.rapidflare.ai/events/plug-and-play.jpeg) Booth only Sep · 22 Embedded systems / IoT hardware ### Embedded World North America Anaheim, CA Sep 22 to 24, 2026 [Visit →](https://embedded-world-na.com/) Sep · 29 Physical security ### IFSEC Expo London, UK Sep 29 to 30, 2026 [Visit →](https://www.boothvision.com/shows/ifsec-international/) Oct · 07 AI · Booth ### World AI Summit Amsterdam, Netherlands Oct 7 to 8, 2026 [Visit →](https://worldsummit.ai/) Oct · 19 Component distribution / electronics · Booth ### ECIA Executive Conference Chicago, IL Oct 19 to 21, 2026 [Visit →](https://www.eciaexecconference.org/) Oct · 20 Physical security ### Securing New Grounds New York, NY Oct 20 to 21, 2026 [Visit →](https://www.securityindustry.org/siaevents/securing-new-ground-2026/) Oct · 27 AI · Booth ### AI for Customer Support Boston, MA Oct 27, 2026 [Visit →](https://events.customersuccesscollective.com/location/aisupport) Nov · 03 Physical security · Booth ### ISC East New York, NY Nov 3 to 5, 2026 [Visit →](https://www.discoverisc.com/east/en-us.html) Nov · 10 Electronics / semiconductor / IoT hardware · Booth ### Electronica Munich, Germany Nov 10 to 13, 2026 [Visit →](https://electronica.de/en/trade-fair/) Dec · 09 AI · Booth ### AI Summit New York New York, NY Dec 9 to 10, 2026 [Visit →](https://newyork.theaisummit.com/) No events match those filters right now. Where we've been ## Recent events Sep · 16 Electronics manufacturing ### Electronica India Bangalore, India Sep 16 to 18, 2026 [Visit →](https://electronica-india.com/en/) Sep · 15 Semiconductor ### AI Infra Summit Santa Clara, CA Sep 15 to 17, 2026 [Visit →](https://ai-infra-summit.com/) Sep · 14 Physical security ### GSX Atlanta, GA Sep 14 to 16, 2026 [Visit →](https://www.gsx.org/) ## Want a live agent on your catalog at your next event? [Book a demo](https://www.rapidflare.ai/contact) --- # News Source: https://www.rapidflare.ai/resources/news > Announcements and writing from the Rapidflare team, and coverage of Rapidflare elsewhere. # News Stay up to date on how Rapidflare is advancing product intelligence and building domain-specific AI agents for the electronics industry. Follow our latest product launches, customer deployments, partnerships, company milestones, and industry insights to see what reliable AI looks like in practice across product discovery, technical sales, support, and business operations. [![The Rapidflare and DEEPX logos side by side on a dark violet ground.](https://www.rapidflare.ai/news/deepx-partnership.avif) Partnership Jul 8, 2026 ### Rapidflare Partners with DEEPX to Drive Technical Intelligence for the Physical AI Ecosystem Establishing Rapidflare's agentic AI infrastructure as the trusted product intelligence layer across DEEPX's software and engineering systems.](https://www.rapidflare.ai/resources/news/deepx-partnership) [![Title card introducing Forge, a new era of agentic AI for the electronics industry.](https://www.rapidflare.ai/news/introducing-forge.avif) Product launch May 15, 2026 ### Rapidflare Brings Long-Running AI Agents to Electronics Industry with Launch of Forge Forge is Rapidflare's agentic AI platform built for electronics, executing complex, multi-step work autonomously over hours and days.](https://www.rapidflare.ai/resources/news/forge-launch) [![Diagram contrasting a tangle of product requirements with an agent answer recommending a matching system-on-module, plus three alternatives.](https://www.rapidflare.ai/news/product-selection.avif) Explainer Apr 24, 2026 ### What is the Rapid Product Selection Agent? AI-powered product selection that helps B2B buyers navigate complex technical catalogs and get accurate, explainable recommendations instantly.](https://www.rapidflare.ai/resources/news/what-is-rapid-product-selection) [![The Rapidflare and McFadyen Digital logos side by side on a dark violet ground.](https://www.rapidflare.ai/news/mcfadyen.avif) Partnership Apr 23, 2026 ### Rapidflare and McFadyen Digital Partner to Accelerate B2B eCommerce with AI Agents Bringing AI Agents to Adobe Commerce, helping electronics manufacturers and distributors simplify technical buying.](https://www.rapidflare.ai/resources/news/mcfadyen-digital-partnership) [![Critical Link title card for its AI-guided SOM recommendation engine, beside a screenshot of the engine recommending two system-on-modules.](https://www.rapidflare.ai/news/critical-link.avif) Customer launch Apr 21, 2026 ### Critical Link Launches World's First AI-Driven SOM Recommendation Engine, Powered by Rapidflare Critical Link launches the first AI-driven SOM recommendation engine to help engineers find embedded solutions faster.](https://www.rapidflare.ai/resources/news/critical-link-som-engine) [![Diagram of engineering documents, diagrams and repositories feeding one Rapidflare layer that serves internal, partner and customer support hubs.](https://www.rapidflare.ai/news/rolling-wireless.avif) Partnership Mar 26, 2026 ### Rapidflare and Rolling Wireless Partner to Transform Technical Support for Connected Automotive Products Unifying automotive and engineering data into an AI support layer that speeds resolution and improves accuracy.](https://www.rapidflare.ai/resources/news/rolling-wireless-partnership) [![Diagram of a PCB photo, schematic, datasheet and technical drawing feeding a visual reasoning panel that identifies and links components.](https://www.rapidflare.ai/news/visual-reasoning.avif) Product launch Feb 25, 2026 ### Introducing the Electronics Industry's First AI Agent with Visual Reasoning A visual-reasoning AI agent turns schematics, pinouts, and diagrams into searchable knowledge, delivering diagram-grounded answers.](https://www.rapidflare.ai/resources/news/visual-reasoning-ai-agent) [![The Rapidflare logo and the Discord logo joined by a two-way arrow.](https://www.rapidflare.ai/news/discord-integration.avif) Integration Jan 21, 2026 ### Rapidflare Launches Native Discord Integration for Scalable Developer Support Native Discord integration helps DevRel teams support large developer communities with accurate, AI-powered responses.](https://www.rapidflare.ai/resources/news/discord-integration-launch) [![SOC 2 Type II title card with a shield and check mark, labeled security, availability, confidentiality and auditability.](https://www.rapidflare.ai/news/soc2-typeII.avif) Compliance Sep 18, 2025 ### Building Enterprise Trust: Rapidflare Achieves SOC 2 Type II Compliance Rapidflare is now SOC 2 Type II attested, enterprise-grade, independently audited security for trustworthy AI agents.](https://www.rapidflare.ai/resources/news/soc-2-type-ii) ## Featured elsewhere [ ### How Rapidflare built a million document ingestion pipeline for agents Temporal engineering blog →](https://temporal.io/blog/how-rapidflare-built-a-million-document-ingestion-pipeline-for-agents-on-temporal)[ ### Four generations of the Rapidflare agent harness Edge AI and Vision Alliance →](https://www.edge-ai-vision.com/2026/06/four-generations-of-the-rapidflare-agent-harness-spark-flame-blaze-and-forge/)[ ### Rapidflare company profile Edge AI and Vision Alliance →](https://www.edge-ai-vision.com/companies/rapidflare/) ## Looking for pricing, a benchmark, or a customer reference? [Get in touch](https://www.rapidflare.ai/contact) --- # Critical Link Launches World's First AI-Driven SOM Recommendation Engine, Powered by Rapidflare Source: https://www.rapidflare.ai/resources/news/critical-link-som-engine > Critical Link launches the first AI-driven SOM recommendation engine to help engineers find embedded solutions faster. [News](https://www.rapidflare.ai/resources/news) # Critical Link Launches World's First AI-Driven SOM Recommendation Engine, Powered by Rapidflare April 21, 2026 Team Rapidflare ![Critical Link title card for its AI-guided SOM recommendation engine, beside a screenshot of the engine recommending two system-on-modules.](https://www.rapidflare.ai/news/critical-link.avif) **San Jose, CA. April 21, 2026**: Critical Link LLC, a leader in system-on-module solutions, has introduced the world’s first AI-driven System on Module Recommendation Engine, powered by Rapidflare’s Rapid Product Selection Agent. The new engine advances Critical Link’s mission to help customers bring embedded products to market faster and more cost-effectively. In the electronics industry, selecting the right product often requires manually comparing hundreds of pages of datasheets or relying on rigid parametric search tools. Critical Link’s SOM Recommendation Engine is set to change that. With Rapidflare’s conversational AI agent, customers can describe their requirements in natural language and receive tailored recommendations in a fraction of the time. “For years customers have asked for a better way to find the right SOM for their application. Launching this AI-driven engine with Rapidflare’s technology is a game changer,” said Amber Thousand, Sr. Director of Marketing at Critical Link. “Their accuracy, domain expertise, and speed of integration made them the clear choice to support our mission.” Unlike generic AI agents, Rapidflare’s technology is purpose-built for complex product selection workflows. It combines knowledge graph-based reasoning, domain-specific intelligence, and industry guardrails to deliver recommendations that are both fast and reliable for electronics teams. “The best partnerships happen when your mission aligns with your partner’s mission,” said Navanee Sundaramoorthy, CEO and Founder at Rapidflare. “We’re proud to partner with Critical Link to help make SOM product selection more smooth, intuitive, and efficient for their team and customers.” Beyond accelerating product selection, the AI engine gives engineers a new way to engage with Critical Link. “We’ve always offered thorough documentation and product support to customers via our website, our engineering wiki, and personal contact. Adding the SOM Recommendation Engine creates a more efficient path for self-discovery, which we see as a growing trend,” said Thousand. “Together, Rapidflare and Critical Link are combining their strengths to make the journey from concept to product faster, smarter, and more closely aligned with customer needs.” To explore Critical Link’s SOM Recommendation Engine, visit [https://www.criticallink.com/som-recommendation-ai-agent/](https://www.criticallink.com/som-recommendation-ai-agent/). To learn more about Rapidflare and its AI-powered product selection solutions, visit Rapidflare’s website: [https://www.rapidflare.ai/](https://www.rapidflare.ai/) ## About Critical Link Critical Link designs and manufactures CPU-based, FPGA-based, and DSP-based system-on-modules (SOMs) for industrial electronic applications. Its production-ready embedded solutions help customers bring products to market faster and at lower cost by reducing development complexity, risk, and time spent building core processing subsystems from scratch. With a focus on product quality, long-term availability, lifecycle support, and close customer engagement, Critical Link serves OEMs across a wide range of industrial and technically demanding applications. For more information, visit the website: criticallink.com ## About Rapidflare Rapidflare builds AI-powered domain specific agents for electronics, semiconductors, and other technically complex industries. Its product intelligence powered AI platform gives teams natural-language access to product and engineering knowledge, making it easier to find accurate answers, support customers, and move faster across critical workflows. Rapidflare multiplies the impact of GTM teams by making critical technical knowledge instantly accessible, helping sales, solutions engineering, product marketing, support, and customer success teams move faster and operate with confidence. For more information, visit rapidflare.ai **Media contact** Balpreet Kaur [balpreet@rapidflare.ai](mailto:balpreet@rapidflare.ai) [All news](https://www.rapidflare.ai/resources/news) --- # Rapidflare Partners with DEEPX to Drive Technical Intelligence for the Physical AI Ecosystem Source: https://www.rapidflare.ai/resources/news/deepx-partnership > Establishing Rapidflare's agentic AI infrastructure as the trusted product intelligence layer across DEEPX's software and engineering systems. [News](https://www.rapidflare.ai/resources/news) # Rapidflare Partners with DEEPX to Drive Technical Intelligence for the Physical AI Ecosystem July 8, 2026 Team Rapidflare ![The Rapidflare and DEEPX logos side by side on a dark violet ground.](https://www.rapidflare.ai/news/deepx-partnership.avif) > - Establishes Rapidflare’s agentic AI infrastructure as the trusted product intelligence layer across DEEPX’s software and engineering systems > - Unifies fragmented documentation, GitHub repositories, and DXNN® SDK resources to deliver instant, verifiable technical support for edge AI developers > - Enables real-time, mission-critical operational guidance for complex robotics and industrial automation deployments Rapidflare, a leading agentic AI infrastructure platform specializing in developer enablement, technical support, and intelligent knowledge orchestration for the electronics industry, today announced a strategic partnership with DEEPX, a pioneer in ultra-low-power Neural Processing Units (NPUs) for Physical AI. Through this collaboration, Rapidflare is deploying its advanced intelligence platform across DEEPX’s developer ecosystem, establishing a trusted product intelligence layer that unifies GitHub repositories, DXNN® SDK documentation, developer resources, and internal engineering systems. ## A Trusted Intelligence Layer for High-Tech Engineering The integration allows developers, customers, and engineering teams to receive instant, accurate answers cited with deep links across fragmented hardware and software knowledge sources. By streamlining access to technical expertise, the platform accelerates development timelines and significantly reduces support friction. As edge AI platforms expand globally across robotics, smart mobility, industrial automation, and intelligent infrastructure, technical knowledge must scale efficiently. Rapidflare is engineered specifically for these complex environments where accuracy and explainability are essential. The platform leverages knowledge graphs, structured reasoning with tool calling, and source-level traceability to transform disparate engineering data into reliable operational intelligence. > “Physical AI systems will increasingly depend on trusted knowledge as much as they depend on compute,” said Prush Palanichamy, Co-Founder and CRO of Rapidflare. “Our work with DEEPX demonstrates how organizations can create a reliable intelligence layer. Long term, we believe this becomes a foundational layer for how Physical AI platforms are built, supported, and continuously improved.” ## Full-Stack Foundation for Physical AI Deployment Together, the companies are delivering a full-stack solution to make physical autonomy highly maintainable. While DEEPX provides the processing backend through its edge AI silicon, including the flagship DX-M1 and the generative AI-focused DX-M2 NPUs, Rapidflare delivers the mission-critical intelligence layer. Rapidflare’s agentic systems ingest the complete technical parameters of a physical product, including schematics, configuration guides, and maintenance logs, to provide real-time guidance. Whether debugging an industrial system in the field, configuring a newly deployed robot, or training operators on complex equipment, the platform ensures the high accuracy required for enterprise environments. > “Scaling Physical AI requires more than breakthrough silicon,” said Tim Park, Strategic Marketing Director at DEEPX. “As our ecosystem grows, developers and customers need fast, reliable access to the knowledge required to build, optimize, and deploy on DEEPX. Rapidflare enables us to deliver that experience while maintaining the accuracy, traceability, and trust required in mission-critical technical environments.” ![Rapidflare and DEEPX team at COMPUTEX 2026](https://www.rapidflare.ai/news/deepx-team-photo.avif) ## Availability and Future Roadmaps The Rapidflare platform is currently live and fully integrated within DEEPX’s technical support, engineering, and developer enablement systems. Moving forward, both companies aim to expand the framework to bridge the gap between documentation and real-world operational feedback. The collaboration establishes the long-term infrastructure necessary for advanced edge devices, such as factory robots and autonomous machinery, to smoothly utilize automated troubleshooting, self-diagnosis, and real-time configuration guidance directly at the edge. To learn more, visit [www.deepx.ai](http://www.deepx.ai) or [www.rapidflare.ai](http://www.rapidflare.ai). ### About Rapidflare Rapidflare is an agentic AI platform built for technical and engineering organizations across the semiconductor, electronics, OEM, and industrial technology sectors. The platform transforms fragmented documentation, engineering systems, product data, and support workflows into trusted operational intelligence. By combining structured knowledge systems, explainable AI, and engineering-aware reasoning, Rapidflare enables organizations to deliver accurate, source-cited answers across complex technical environments. ### About DEEPX DEEPX is a leading on-device AI semiconductor company dedicated to democratizing Physical AI at the edge. Powered by its proprietary NPU architecture, DEEPX delivers high-performance, ultra-low-power solutions that enable edge devices to process sophisticated workloads, from real-time computer vision to on-device LLMs, locally. DEEPX empowers industries, from robotics to smart cities, to unlock new possibilities with energy-efficient, secure, and cost-effective intelligence. Visit [www.deepx.ai](http://www.deepx.ai) ### Media Contacts DEEPX: Ella Lee, PR & Marketing Manager [pr@deepx.ai](mailto:pr@deepx.ai) Rapidflare: Balpreet Kaur, PR & Marketing Manager [balpreet@rapidflare.ai](mailto:balpreet@rapidflare.ai) [All news](https://www.rapidflare.ai/resources/news) --- # Rapidflare Launches Native Discord Integration for Scalable Developer Support Source: https://www.rapidflare.ai/resources/news/discord-integration-launch > Native Discord integration helps DevRel teams support large developer communities with accurate, AI-powered responses. [News](https://www.rapidflare.ai/resources/news) # Rapidflare Launches Native Discord Integration for Scalable Developer Support January 21, 2026 Vasanth Asokan ![The Rapidflare logo and the Discord logo joined by a two-way arrow.](https://www.rapidflare.ai/news/discord-integration.avif) Discord has evolved from a simple chat application into a core collaboration layer for many developer communities. Originally adopted in gaming contexts, it now serves as a shared workspace for technically oriented ecosystems, particularly in hardware, infrastructure, and open-source domains, where developers don’t just ask questions, but form communities, establish norms, and build a sense of long-term affiliation around products they use and trust. For DevRel teams, this makes Discord a surface that’s difficult to ignore. Today, we’re announcing **Rapidflare’s native Discord integration**, built to help companies support large, public developer communities with speed, consistency, and technical credibility across every stage of adoption. ## Why More Technical and Hardware Teams Are Building on Discord Discord has become the commons where developer communities form, share knowledge, and build long-term affiliation. **Always-on developer experience:** For DevRel teams, Discord functions like a **live support floor** rather than a ticket queue. Questions surface instantly in public channels, conversations unfold in real time, and community members often help one another before staff step in. As communities grow, keeping this experience consistent becomes a scaling challenge. **High-signal feedback loops:** Discord acts as a **stethoscope on developer sentiment**. Release issues, confusion, and excitement show up immediately through conversation and reactions, giving DevRel teams early insight that dashboards and issue trackers alone can’t provide. **Community-driven onboarding and retention:** For many products, Discord is the **first room developers walk into** after installation. Roles, channels, and guided flows shape how developers get oriented, learn best practices, and decide whether to stay engaged over time. Taken together, Discord is no longer just a communication channel, it has become a **core DevRel surface**, spanning onboarding, support, feedback, and long-term community building. ## What the Rapidflare Discord Integration Enables Rapidflare brings AI-powered technical intelligence directly into Discord, allowing teams to respond to developer questions using verified documentation and internal knowledge. With the integration, companies can: - Deliver accurate, consistent technical answers at scale - Reduce response times without sacrificing depth - Support thousands of developers without linear headcount growth - Maintain a single source of technical truth across channels The result is a Discord community that remains responsive, credible, and scalable as adoption grows. ## Built for Production-Scale Communities Rapidflare’s Discord integration was designed for real-world usage, including large, public servers with thousands of active users. Key capabilities include: - Enterprise-grade authentication and access control - Protection against abuse and spam - Support for different community workflows and channel types - Optional white-labeling for customer-branded bots These features make the integration suitable not only for support teams, but also for product, sales engineering, and developer-facing roles that operate in public forums. ## One Platform, Multiple Collaboration Channels Discord joins Rapidflare’s growing ecosystem of integration with collaboration tools: ✅ [Slack](https://docs.rapidflare.ai/deploying/slack), supported today ✅ [Discord](https://docs.rapidflare.ai/deploying/discord), supported today 🔜 Microsoft Teams, coming soon This allows companies to centralize technical knowledge while engaging developers and customers where conversations already happen. ## Looking Ahead As technical products become more complex and community-driven, the quality of developer engagement increasingly determines market success. Rapidflare’s Discord integration is a step toward helping teams scale that engagement, with consistency, credibility, and confidence, wherever developers choose to gather. [All news](https://www.rapidflare.ai/resources/news) --- # Rapidflare Brings Long-Running AI Agents to Electronics Industry with Launch of Forge Source: https://www.rapidflare.ai/resources/news/forge-launch > Forge is Rapidflare's agentic AI platform built for electronics, executing complex, multi-step work autonomously over hours and days. [News](https://www.rapidflare.ai/resources/news) # Rapidflare Brings Long-Running AI Agents to Electronics Industry with Launch of Forge May 15, 2026 Team Rapidflare ![Title card introducing Forge, a new era of agentic AI for the electronics industry.](https://www.rapidflare.ai/news/introducing-forge.avif) Rapidflare, the agentic AI platform purpose-built for electronics distributors and OEMs, today announced the launch of **Forge**, its fourth-generation AI agent architecture. Forge moves beyond real-time sales conversations into long-running, autonomous workflows, enabling electronics distributors to automate complex, multi-day tasks that previously required significant sales engineering time. In electronics distribution, a single sales engagement can touch hundreds of part numbers, require cross-referencing datasheets against application-specific requirements, and span weeks before a proposal is ready. The work is complex, multi-step, and doesn’t fit in a single conversation. Forge is built precisely to handle such tasks. Running on top of Rapidflare’s proven **Blaze** harness, already in production for real-time product selection, cross-reference, proposals, and technical support, Forge adds a persistent execution layer capable of running tasks for hours or days, with sleep and wake cycles, file system access across sessions, and native connectivity to CRM, email, Slack, and enterprise tools. Forge is the fourth generation of Rapidflare’s agent architecture, following Spark (2023), Flame (2024), and Blaze (2025). > “We’ve been moving our own AI frontier at least every six months. Every generation of our harness builds upon the previous, accounting for learnings and frontier model evolutions, and Forge is the most powerful expression of that yet.” Forge is currently available to a select group of enterprise customers by invitation only. Electronics distributors and OEMs interested in early access can [register their interest](https://www.rapidflare.ai/contact) through Rapidflare’s contact page. [All news](https://www.rapidflare.ai/resources/news) --- # Rapidflare and McFadyen Digital Partner to Accelerate B2B eCommerce with AI Agents Source: https://www.rapidflare.ai/resources/news/mcfadyen-digital-partnership > Bringing AI Agents to Adobe Commerce, helping electronics manufacturers and distributors simplify technical buying. [News](https://www.rapidflare.ai/resources/news) # Rapidflare and McFadyen Digital Partner to Accelerate B2B eCommerce with AI Agents April 23, 2026 Team Rapidflare ![The Rapidflare and McFadyen Digital logos side by side on a dark violet ground.](https://www.rapidflare.ai/news/mcfadyen.avif) ## The Partnership Rapidflare and **McFadyen Digital** have announced a strategic collaboration to bring AI Agents to B2B eCommerce platforms. This partnership combines Rapidflare’s AI-powered product intelligence with McFadyen’s expertise in Adobe Commerce implementation to help manufacturers and distributors improve their online sales performance. ## The B2B Conversion Challenge Complex technical product companies face persistently low eCommerce conversion rates, typically between 1-2%. Buyers struggle with analysis paralysis when evaluating datasheets and specifications, while rigid parametric filters frequently fail to identify appropriate products. This creates website abandonment, cart desertion, and revenue loss. Order processing, meanwhile, remains largely manual, with pre-sales engineers spending time on routine inquiries rather than strategic accounts. ## The Solution: Intelligent Agents Rather than static filter navigation, Rapidflare’s AI Agents engage buyers through natural conversation, understanding requirements and guiding them toward confident purchases. These agents integrate with Adobe Commerce and leverage proprietary knowledge graphs to understand products deeply. > “B2B buyers deserve intuitive, intelligent experiences. Our AI Agents understand products the way seasoned sales engineers do.” ## Key Benefits The partnership promises to double web conversion rates, increase average deal size through targeted cross-selling and upselling, and automate routine specification inquiries so technical staff can focus on high-value accounts. ## Availability The solution is immediately available to B2B companies using Adobe Commerce. [All news](https://www.rapidflare.ai/resources/news) --- # Rapidflare and Rolling Wireless Partner to Transform Technical Support for Connected Automotive Products Source: https://www.rapidflare.ai/resources/news/rolling-wireless-partnership > Unifying automotive and engineering data into an AI support layer that speeds resolution and improves accuracy. [News](https://www.rapidflare.ai/resources/news) # Rapidflare and Rolling Wireless Partner to Transform Technical Support for Connected Automotive Products March 26, 2026 Team Rapidflare ![Diagram of engineering documents, diagrams and repositories feeding one Rapidflare layer that serves internal, partner and customer support hubs.](https://www.rapidflare.ai/news/rolling-wireless.avif) **San Jose, CA. March 26, 2026**: Rapidflare and Rolling Wireless today announced a strategic partnership to transform technical support for the connected automotive sectors. By deploying Rapidflare’s product intelligence platform, Rolling Wireless is addressing a challenge in advanced, software-defined hardware: critical technical knowledge across multiple systems, slowing down the teams who need it most. In automotive and industrial environments, technical knowledge is continuously evolving given rapid development cycles. It lives across Jira tickets, Confluence pages, SharePoint repositories, and architectural diagrams, forcing support teams to spend time consolidating information to address customer requests. As vehicles and devices grow more software-defined, tools to integrate these knowledge sources can accelerate operations. Rapidflare bridges these data sources by combining knowledge graphs with visual reasoning to map the relationships between components, engineering changes, and system dependencies. The result is a natural-language interface that gives both internal teams and customers instant access to context-aware, reliable answers, without needing to know where the information lives. ## Making Fragmented Knowledge Instantly Actionable “As automotive products transition toward software-defined architectures, the volume of technical metadata is exploding,” said Navanee Sundaramoorthy, CEO of Rapidflare. “Companies don’t need another search tool, they need a way to make fragmented knowledge instantly actionable. Our platform doesn’t just find documents; it understands the engineering context behind them.” For Rolling Wireless, the impact went beyond the original project scope. “The Rapidflare team’s responsiveness allowed us to extend the solution’s capabilities well beyond what we initially planned,” said Thierry Uguen, VP of Product Management and Support at Rolling Wireless. “We now have a tailored platform that directly supports our goal of delivering faster, high-accuracy technical support to our global customers.” ## A Multi-Tier Intelligence Platform Built for Scale Rapidflare partnered with Rolling Wireless to deploy a multi-agent knowledge platform tailored to different support audiences. The system delivers dedicated, context-aware AI assistance to OEM partners, V2X customers, and internal support teams, each with access to the documentation, configurations, and guidance most relevant to their needs. This approach reduces repetitive inquiries, accelerates resolution times, and ensures consistent, high-quality support across every interaction. As cellular connectivity becomes standard in modern mobility, the platform positions Rolling Wireless at the forefront of AI-driven operational efficiency. ### About Rapidflare Rapidflare is an AI product intelligence platform purpose-built for electronics, semiconductor, and other technically complex enterprises. In industries where knowledge spans chip architectures, firmware ecosystems, hardware revisions, and dense regulatory documentation, Rapidflare transforms fragmented engineering data into a single, queryable intelligence layer. By combining knowledge graphs with visual reasoning, Rapidflare enables technical teams to access and interpret complex documentation through natural language, reducing time-to-resolution, improving data reliability, and unlocking the full value of institutional engineering knowledge. Learn more at rapidflare.ai ### About Rolling Wireless Rolling Wireless is the world’s leading supplier of network access devices (NADs) to the automotive industry, with over 60 million automotive-grade cellular modules shipped to date. In addition to NADs, its portfolio also includes V2X, Wi-Fi/Bluetooth connectivity, and automotive-grade software solutions. Building on more than two decades of innovation and operational excellence, Rolling Wireless helps automotive OEMs and Tier 1 suppliers create applications that enhance safety, delight drivers, and generate additional revenue. Learn more at rollingwireless.com **Media contact** Balpreet Kaur [balpreet@rapidflare.ai](mailto:balpreet@rapidflare.ai) [All news](https://www.rapidflare.ai/resources/news) --- # Building Enterprise Trust: Rapidflare Achieves SOC 2 Type II Compliance Source: https://www.rapidflare.ai/resources/news/soc-2-type-ii > Rapidflare is now SOC 2 Type II attested, enterprise-grade, independently audited security for trustworthy AI agents. [News](https://www.rapidflare.ai/resources/news) # Building Enterprise Trust: Rapidflare Achieves SOC 2 Type II Compliance September 18, 2025 Vasanth Asokan & Prush P ![SOC 2 Type II title card with a shield and check mark, labeled security, availability, confidentiality and auditability.](https://www.rapidflare.ai/news/soc2-typeII.avif) Rapidflare has achieved **SOC 2 Type II** compliance, validating its commitment to enterprise-grade security for AI agents serving the electronics sales industry. The attestation demonstrates that the company’s systems undergo continuous, independently audited security verification. At Rapidflare, our mission has been clear from day one: to build enterprise-ready, explainable, trustworthy, and reliable AI agents that accelerate sales in the electronics industry. From the beginning, we understood that delivering true value to our customers meant keeping security and integrity at the core of everything we do. Today, we’re proud to announce that this commitment has been validated: Rapidflare has successfully achieved SOC 2 Type II compliance. This compliance ensures that sales teams, dealers, and distributors in the electronics space can operate with confidence, knowing that their data and workflows are protected by enterprise-grade security, independently audited and verified over time. ## What SOC 2 Type II Means for Customers - **Peace of mind**: sensitive data is protected by rigorously tested security controls. - **Resilient AI infrastructure**: AI systems reliably scale with complex sales workflows. - **Trusted differentiation**: organizations gain a secure, enterprise-ready partner in competitive markets. ## The SOC 2 Type II Journey For many new startups, the compliance journey can feel like a black box in the early days. Having now gone through the full lifecycle ourselves, we’ve gathered a number of key learnings that we’ll be sharing soon so others can benefit from our experience. A crucial part of this journey has been the support of our compliance partners. We truly could not have done it without them, and we strongly recommend their expertise to any business considering its own compliance path. [Vanta](https://www.vanta.com/), As our trust management platform, Vanta automated security monitoring across our technology stack, giving us real-time visibility into compliance posture and establishing a continuous loop of security aligned with regulatory requirements and AI safety standards. Vanta’s SaaS product is beautifully designed, has a clear starter guide and sections for Tests, Documents, Vendors, Personnel, Controls, Audits etc. Their CS team is knowledgeable, very responsive and ultimately made the learning curve simple. [Johanson LLP](https://www.johansonllp.com/), As our independent auditor, Johanson LLP provided deep expertise in SOC reporting. Their precision and guidance ensured that our controls met, and exceeded, SOC 2 benchmarks. Their Customer Success team was incredible and created tremendous clarity, helped bust myths. The team was always approachable and a pleasure to work with. ## What’s Next SOC 2 Type II is not the finish line, it’s the foundation. At Rapidflare, we remain committed to building the most trusted AI agents in sales. This compliance is one more step in ensuring that our customers always have secure, reliable, and traceable AI support they can count on. [All news](https://www.rapidflare.ai/resources/news) --- # Introducing the Electronics Industry's First AI Agent with Visual Reasoning Source: https://www.rapidflare.ai/resources/news/visual-reasoning-ai-agent > A visual-reasoning AI agent turns schematics, pinouts, and diagrams into searchable knowledge, delivering diagram-grounded answers. [News](https://www.rapidflare.ai/resources/news) # Introducing the Electronics Industry's First AI Agent with Visual Reasoning February 25, 2026 John Williams, Chief Scientist ![Diagram of a PCB photo, schematic, datasheet and technical drawing feeding a visual reasoning panel that identifies and links components.](https://www.rapidflare.ai/news/visual-reasoning.avif) AI has made extraordinary progress in understanding language. But in industries like semiconductors, electronics, manufacturing, medical devices, and infrastructure, language represents only a slice of the knowledge. The most critical technical knowledge is often not written in paragraphs. It is **drawn**. It lives in functional block diagrams, timing charts, pinout drawings, performance graphs, architecture slides, mechanical specifications, and configuration screenshots. Most AI systems simply cannot reason over that content. At Rapidflare, we’ve developed a **Visual Reasoning** capability for AI agents that makes diagrams and other image-like technical artifacts first-class knowledge objects, enabling extraction, multi-modal retrieval, and grounded explanation directly from the visual source. ## Why Text-Only RAG Falls Short for Electronics Teams Most enterprise RAG pipelines are built around text. When electronics documents are ingested, PDFs are flattened, slide decks reduced to bullet points, and critical visuals treated as images rather than structured technical data. As a result, retrieval misses what engineers need. In deep technical domains such as electronics and semiconductors, diagrams aren’t decoration, they’re the specification. When critical details live in a schematic, AI must interpret that visual directly. If artifacts aren’t searchable and retrievable, responses tend to be incomplete, harder to verify, and less useful in design, debug, and operational workflows. ## Applying Visual Reasoning to Electronics Content Visual Reasoning requires three core capabilities, each a significant systems challenge. ### Visual Extraction at Ingestion Extracting images from enterprise documents requires a deliberate approach to preserve meaning. PDFs and slide decks contain raster imagery, vector-based diagrams, clipped regions, transparent overlays, and composite figures. PowerPoint slides are structured visual compositions with cropped figures, masked shapes, callouts, and layered transparency. Engineers rely on structured visual compositions that convey technical intent. Making this usable for AI requires preserving layout, hierarchy, and relationships between elements, moving beyond raw asset extraction toward structure-aware visual reconstruction that maintains semantic and spatial fidelity. ### Multi-Modal Retrieval Across Text and Images Once visuals become first-class knowledge objects, the next challenge is retrieval. Traditional RAG chunks text, generates embeddings, performs nearest-neighbor search, and prompts an LLM with retrieved text. This works for prose, but images require semantic alignment with human technical queries. Visual Reasoning retrieval incorporates vision-language embeddings, structured descriptions generated from diagrams, metadata such as product names and hierarchy, and linkage between images and surrounding explanatory text. Text and visuals must exist in the same conceptual search space, or tightly linked ones that can be reasoned over jointly. ### Contextual Multimedia Response Generation Even if you can extract and retrieve visuals, presentation matters. A good enterprise response should feel like a domain expert guiding the user: introducing the concept, referencing the right diagram at the right moment, using visuals to clarify relationships, and grounding explanations in evidence. The agent must construct a narrative that weaves together reasoning and visual proof, not simply retrieve assets. This requires orchestration logic, ranking strategies, layout intelligence, and response composition that treats visuals as core knowledge. ## Visual Reasoning in Practice: Raspberry Pi Examples We ingested a public Raspberry Pi corpus, datasheets, product guides, mechanical drawings, and educational slide decks, and ran representative queries across it. **How do I set up decoupling capacitors for the RP2040?** The response includes specific values taken directly from the schematic, not from surrounding text. Capacitor values and annotations that appear only in the image are extracted into structured text, and the original visual is returned as evidence. It also captures design intent embedded in the diagram, such as placement instructions. **A basic question for someone new to the platform.** The key difference here is grounding. The image and supporting explanation aren’t from general knowledge, they’re retrieved from the specific ingested slide deck. That’s the distinction between a general chatbot and a vertical agent: the response is based on a controlled, curated corpus, so the factual basis is explicit and traceable. **Designing a case for a Raspberry Pi 4 and needing mounting information.** The agent retrieves the correct mechanical drawing, extracts required dimensions and constraints directly from the diagram, and includes full references for verification against the original. ## The Practical Payoff Bringing visuals into RAG isn’t a small feature. It expands what an enterprise knowledge system can reliably capture and use, especially in electronics. It improves document parsing and visual reconstruction, multi-modal embeddings and figure-level retrieval, linking visuals to surrounding text and hierarchy, storage and indexing for rich media at scale, and response composition that keeps answers traceable to figures. In electronics, the specification is as much visual as it is textual. If an AI system can’t reliably retrieve and reason over schematics, pinouts, timing diagrams, plots, and drawings alongside surrounding text, it will plateau at summaries. And in engineering contexts, summaries rarely change outcomes. A picture can tell a thousand words, but only if you can ask it the right questions and verify the answer against the original figure. [All news](https://www.rapidflare.ai/resources/news) --- # What is the Rapid Product Selection Agent? Source: https://www.rapidflare.ai/resources/news/what-is-rapid-product-selection > AI-powered product selection that helps B2B buyers navigate complex technical catalogs and get accurate, explainable recommendations instantly. [News](https://www.rapidflare.ai/resources/news) # What is the Rapid Product Selection Agent? April 24, 2026 Team Rapidflare ![Diagram contrasting a tangle of product requirements with an agent answer recommending a matching system-on-module, plus three alternatives.](https://www.rapidflare.ai/news/product-selection.avif) For companies selling technically complex products, sales teams spend more time answering “which product is right for me?” than almost anything else. Rapid Product Selection Agent changes that, turning every product question into qualified pipeline and freeing reps to focus on what closes deals: strategic selling. ## The Problem with Electronics Product Discovery In electronics, semiconductors, and industrial equipment, picking the right product is never simple. Catalogs are vast. Specs are dense. One wrong selection can cost a customer months of rework, and cost your team the deal. So where does that complexity go? It gets absorbed by your people. Sales engineers answering the same questions, again and again. Solutions engineers dragged into early-stage conversations they shouldn’t be in yet. Customer success teams guessing their way through a catalog instead of confidently guiding customers through it. Your best technical talent, buried in work that shouldn’t require them. ## How We’re Fixing It Rapid Product Selection Agent is a conversational AI that understands your catalog the way your best sales engineer does, not as a list of specs, but as a body of knowledge about what each product does, who it’s for, and why it beats the alternative. It is domain-tuned, not model-trained. Your catalog and documents are extracted into a knowledge graph the agent retrieves from, and your data never adjusts any model’s weights. It knows your industry’s vocabulary, understands the trade-offs your buyers care about, and stays within the boundaries of your catalog. It doesn’t guess. It doesn’t go off-script. It reasons, and it shows its work. Traditional product discovery With Rapid Product Selection Agent Manual datasheet comparison Natural language requirements Rigid parametric search filters Instant, reasoned recommendations Sales engineer pulled in early Self-service for early-stage buyers Slow response to inbound questions 24/7 accurate product guidance Expertise locked inside individuals Expertise available to every team member Buyers leave when they can’t self-serve Buyers arrive better informed, further along ## How Rapid Product Selection Agent Works Rapid Product Selection Agent combines three layers that generic AI tools lack: a knowledge graph of your product catalog, domain-specific intelligence tuned to your industry, and guardrails that keep every recommendation accurate and on-catalog. ### Natural language understanding Buyers describe what they need in plain English, processor performance, temperature range, form factor. The agent maps intent to the right products without requiring search syntax or catalog expertise. ### Knowledge graph reasoning No keyword matching. The agent reasons across structured relationships between products, specifications, and applications, surfacing trade-offs the way an expert engineer would, at the speed of a search engine. ### Domain-specific guardrails Every recommendation is real, available, and relevant. No out-of-catalog suggestions. When the agent cannot ground an answer in your catalog, it says so instead of guessing. ### Contextual conversation Follow-up questions build on prior context. A buyer asking “what about operating temperature?” gets a precise, contextual answer, not a fresh search from scratch. ### Scalable expertise The knowledge inside your best engineers gets encoded once, and made available to every prospect and customer, simultaneously. Your top performer, available 24/7, at infinite scale. ## Built for Every Revenue-Facing Team Product complexity doesn’t just slow down sales, it creates drag across your entire GTM org. Here’s where Rapid Product Selection Agent removes it. Team What changes **Sales teams** Spend less time on early qualification. Prospects arrive better informed and further along in the buying process. **Solutions engineers** Get pulled in later, for conversations that need them. Fewer repetitive first calls. **Product marketing** Product knowledge reaches buyers directly, without relying on sales to communicate it perfectly each time. **Customer success** Fewer support escalations on basic product questions. Customers self-serve with confidence. ## Product Selection Agent vs. Parametric Search vs. Generic AI These three approaches are often conflated. They solve fundamentally different problems. **Parametric search** requires buyers to think like engineers, defining every variable upfront and filtering by exact spec. That works for expert buyers in routine situations. It fails everyone else, especially early in a design cycle when requirements are still forming. **Generic AI** can converse, but it cannot reason reliably about technically complex trade-offs. It hallucinates specs. It recommends products that don’t exist. For technical B2B catalogs, that destroys trust faster than no AI at all. **Rapid Product Selection Agent** combines the structure of parametric search with the accessibility of conversational AI, and adds the domain-specific reasoning that neither approach can offer on its own. It’s not a better search. It’s a different category entirely. ## Real-World Example: Critical Link Critical Link, a leader in system-on-module design and manufacturing for industrial electronics, recently launched the world’s first AI-driven SOM Recommendation Engine, powered by Rapid Product Selection Agent. > _“Their accuracy, domain expertise, and speed of integration made them the clear choice to support our mission.”_ Engineers visiting Critical Link’s website can now describe their embedded design requirements in plain language and receive tailored recommendations in seconds, with reasoning surfaced alongside every result. The same capability is available to any company where a technically complex catalog meets a buyer who needs guidance: semiconductors, test and measurement, specialty components, industrial equipment, and beyond. If you’re ready to give every buyer the same experience Critical Link now delivers, let’s talk. [Book a 15 min chat](https://calendar.google.com/calendar/u/0/appointments/schedules/AcZssZ2FjwFzkdjEaRhlU8klHQgkbSH0310blhbdPeDyoi5TaLi-703wcT3LNH08D-VLeAhGK9BBfBu-). ## Frequently Asked Questions ### What is Rapid Product Selection Agent? Rapid Product Selection Agent is an AI-powered experience that helps buyers find the right product from a complex catalog by describing requirements in natural language and returning accurate, reasoned recommendations. Unlike parametric search or generic AI chatbots, it uses domain-specific knowledge and structured reasoning to handle technically complex product decisions, accurately, instantly, and at scale. ### What industries benefit most from Rapid Product Selection Agent? The strongest fits are industries where products are technically complex, catalogs are large, and buyers need to match specifications to a specific use case, electronics, semiconductors, industrial equipment, test and measurement, specialty components, and scientific instrumentation. If your buyers regularly ask “which product is right for me?”, the answer is probably your industry. ### How is Rapid Product Selection Agent different from generic LLM chat experiences? Generic LLMs are conversational but lack the specialized knowledge and constraints needed for technical product selection. They hallucinate specifications, recommend products that don’t exist, and give inconsistent answers to the same question. A Product Selection Agent works from your specific catalog, uses structured reasoning within defined boundaries, and provides explainable recommendations with consistent accuracy. It’s the difference between asking a generalist for technical advice and consulting a specialist engineer who knows your exact product line. ### How long does it take to deploy? Rapidflare is purpose-built for fast integration. The Critical Link deployment went from signed agreement to live product in days, not months. Timelines vary based on catalog complexity and use case, but speed of deployment is a core part of what we deliver. Reach out to discuss what that looks like for your organization. [All news](https://www.rapidflare.ai/resources/news) --- # Customer stories Source: https://www.rapidflare.ai/resources/stories > The people behind the deployments. Until the first stories publish, the case studies carry the proof. Customer stories # The people behind the deployments Stories are the human register: how a team changed the way it works. The first ones are being written with customers now. Until they publish, the case studies carry the proof, with the numbers attached. [Read the case studies](https://www.rapidflare.ai/customers) Meanwhile, the proof ## From the case study library [ 30% · Fewer Level 1 support queries Global access-control leader ### An access-control leader cut Level 1 support queries by 30% One agent grounded in a cleaned-up knowledge base now answers support teams, SaaS users, and resellers, powering 10,000 conversations a month. - Physical security and access control - Technical support - Sales - OEM ](https://www.rapidflare.ai/customers/access-control)[ 99,000+ · Authorized dealer and integrator product questions supported Cloud-managed video surveillance provider ### How a cloud-managed video surveillance solution provider made its product expertise instantly accessible across its dealer and integrator channel Authorized security dealers and integrators ask technical questions in natural language and get answers grounded in the company's own product knowledge. - Physical security and access control - Technical support - Sales - OEM ](https://www.rapidflare.ai/customers/alibi)[ 9,000+ · AI-assisted interactions in the first seven months Security Industry Association ### How SIA scaled access to trusted industry knowledge with askSIA The security industry's standards authority turned its reference library into a site-wide AI answer layer, without giving up the rigor its members rely on. - Physical security and access control - Marketing ](https://www.rapidflare.ai/customers/sia)[ 3 systems · DEEPX systems on one intelligence layer: technical support, engineering, and developer enablement DEEPX ### DEEPX put its SDK, repositories, and engineering docs behind one answer layer The NPU maker unified DXNN SDK documentation, GitHub repositories, and internal engineering systems into one cited answer layer for edge AI developers. - Semiconductor - Industrial and manufacturing - Technical support - OEM ](https://www.rapidflare.ai/customers/deepx) ## Looking for pricing, a benchmark, or a customer reference? [Get in touch](https://www.rapidflare.ai/contact) --- # About Source: https://www.rapidflare.ai/about > The people behind Rapidflare: four co-founders out of Xilinx and the embedded world, building accurate AI agents for technical sales and support in electronics. About # We came from the industry we build for Four founders out of Xilinx and the embedded world, who spent careers watching the right answer sit trapped in a datasheet. Rapidflare is what we built to get it out. [Book a demo](https://www.rapidflare.ai/contact) [See the proof](https://www.rapidflare.ai/customers) Based in · Silicon Valley, working with customers across the US, Europe, and Asia Backing · Venture backed, with investors who know enterprise and deep tech Security · SOC 2 Type II, with audited controls and your data kept yours The through line · All four founders came up through Xilinx and the embedded world Why we are here ## Deep product expertise, in every action your business takes That is the whole goal: curated, structured knowledge joined to AI agents that are accurate and pointed at an outcome. Electronics runs on documentation that no one has time to read. > The person who knows the answer is always the busiest person in the building. The founders ## Four people who have been on your side of the table Between them: FPGA silicon, embedded Linux, streaming platforms at Netflix scale, and two decades of selling technical product to engineers. Every one of them has shipped into this industry, and three have sold a company to someone in it. ![Navaneethan Sundaramoorthy](https://www.rapidflare.ai/team/navanee.jpg) ### Navaneethan Sundaramoorthy CEO and co-founder Xilinx · → · Uncanny Vision · → · Eagle Eye Networks Built award-winning hardware and software at Xilinx, then co-founded Uncanny Vision, a computer vision AI company acquired by Eagle Eye Networks. ![Vasanth Asokan](https://www.rapidflare.ai/team/vasanth.jpg) ### Vasanth Asokan CTO and co-founder Xilinx · → · Netflix · → · Rapidflare Senior platform leadership at Netflix, product management, technical strategy, architecture for large scale distributed systems, developer experience, embedded engineering at Xilinx. ![Prush Palanichamy](https://www.rapidflare.ai/team/prush.jpg) ### Prush Palanichamy CRO and co-founder Honeywell · → · Xilinx · → · Sierra Wireless Twenty years of technical product sales and marketing across Honeywell, Xilinx, Sierra Wireless, and startups that got acquired. ![Dr. John Williams](https://www.rapidflare.ai/team/john.jpg) ### Dr. John Williams CSO and co-founder Petalogix · → · Xilinx · → · Rapidflare Founded Petalogix, an embedded Linux startup acquired by Xilinx. Pairs research depth with the experience of shipping to industry. What we hold to ## Three things we will not trade away Accuracy first ### A plausible answer is the wrong answer In electronics, a spec that is nearly right puts the wrong part in a customer’s hands. We built for extraction accuracy before anything else, and we publish the benchmark and the method behind it. Show the source ### Every answer cites where it came from A rep will not stake a deal on a black box. Each answer traces back to the document it came from, so trust is something you can check rather than something you extend. External by design ### Built for your customers, not your staff Internal assistants answer employees. Our agents sit on your site and in front of your customers and channel, which is a higher bar for both accuracy and tone. Backing ## Who is behind us ![Mucker Capital](https://www.rapidflare.ai/investors/mucker.png) ![Struck Capital](https://www.rapidflare.ai/investors/struck.png) ![z21 Ventures](https://www.rapidflare.ai/investors/z21.png) ![Rebright Partners](https://www.rapidflare.ai/investors/rebright.png) ![Upekkha](https://www.rapidflare.ai/investors/upekkha.png) ![500](https://www.rapidflare.ai/investors/500.png) We are hiring ### Engineering and go to market If you know this industry and want to work on the accuracy problem, we want to hear from you. [Get in touch](https://www.rapidflare.ai/contact) Keep reading ## Related [Proof ### Customers The results, by the numbers, from teams in the electronics industry. ](https://www.rapidflare.ai/customers)[Product ### Product intelligence The layer that turns your documentation into answers. ](https://www.rapidflare.ai/product/product-intelligence)[Method ### Accuracy benchmark How we measured 95% extraction accuracy, and against what. ](https://www.rapidflare.ai/methodology) Get started ## Bring us a document that usually breaks AI We’ll ingest your own documentation and show you what an agent can do with it, on your products, with a source on every line. [Book a demo](https://www.rapidflare.ai/contact) [Read the benchmark method](https://www.rapidflare.ai/methodology) SOC 2 Type II  ·  Every answer traceable to its source --- # Contact Source: https://www.rapidflare.ai/contact > Talk to Rapidflare. Bring us a product family and see the agent answer questions about your own parts on a 30 minute call. Contact # Bring us your hardest product questions The best evaluation is the agent answering questions about your own parts. Tell us a little about your catalog and we will set that up. 1 ## We reply within one business day A person, not a sequence. We will ask for a slice of your documentation, a product family is enough. 2 ## We build on your real documents We ingest the slice and build the graph, before any contract. 3 ## You grill the agent on a 30 minute call It answers your questions about your parts, which beats any demo catalog. --- # Pricing Source: https://www.rapidflare.ai/pricing > Rapidflare pricing scales with your catalog and your team. Every plan is scoped with our team first: the number you see is the number you pay. Pricing # Three ways to start Plans are based on the size of your product catalog and the number of users. We scope each plan with you upfront, so you know exactly what's included. ### Basic One agent, one job. For a team proving the value on a focused slice of the catalog. - Marketing site and full-screen deployment - Conversation history and usage analytics - Onboarding QA and initial accuracy tuning - Email support Up to 3 sources · 1 integration · Quarterly accuracy report · 5 customer success hours per month [Talk to sales](https://www.rapidflare.ai/contact) Most teams start here ### Professional The agent shows up where your people already work, and you control what it says. - Embed in Slack, Zendesk, and partner portals - Rich artifacts: comparison tables, proposal docs - Admin tuning and controllable outcomes - Content gap analysis and advanced analytics Up to 5 sources · 2 integrations · Monthly accuracy report · 20 customer success hours, SSO, dedicated CSE [Talk to sales](https://www.rapidflare.ai/contact) ### Enterprise Many agents, many audiences, wired into the systems that run your business. - Agent hubs, one per use case - Workflow automation, lead capture, CRM handoff - Human in the loop on high-stakes answers - Bill of materials generation Unlimited sources · Unlimited integrations · Continuous accuracy evaluation · 50+ customer success hours, FDE team [Talk to sales](https://www.rapidflare.ai/contact) Every plan · Hallucination control · Structured reasoning · A source on every answer · Multilingual · Comparison across datasheets ### Scoped with our team first Plans are sized against your real catalog and seats, so a distributor with ten seats and an OEM with a global channel do not pay the same way. ### The number you see is the number you pay No per-question metering surprise. Usage grows with your team. ### Start on Basic, no lock-in Prove the value on a focused slice of the catalog, then move to Professional or Enterprise when your team is ready. ## Not sure what’s right for your use case? [Talk to sales](https://www.rapidflare.ai/contact) --- # Privacy Policy Source: https://www.rapidflare.ai/privacy > How Rapidflare collects, uses, and protects personal information. Legal # Privacy Policy Last revised September 9, 2026 This privacy notice for **Rapidflare, Inc.** (“Rapidflare,” “we,” “us,” or “our”) describes how and why we collect, store, use, and share (“process”) your information when you: - Visit our website at [https://www.rapidflare.ai](https://www.rapidflare.ai), or any website of ours that links to this notice. - Use the Rapidflare Dashboard at [https://dashboard.rapidflare.ai](https://dashboard.rapidflare.ai). - Interact with a Rapidflare AI agent, whether on our website or deployed on a customer’s website or support channel. - Engage with us in other related ways, including any sales, marketing, or events. **Questions or concerns?** If you do not agree with our policies and practices, please do not use our Services. If you have questions, contact us at [support@rapidflare.ai](mailto:support@rapidflare.ai). ## Summary - **What personal information do we process?** Contact details you give us, information collected automatically when you use our Services (including IP address and usage data), and conversation content when you interact with a Rapidflare agent. - **Do we process sensitive personal information?** No. - **Do we receive information from third parties?** Yes, from analytics and business-intelligence providers, and from our enterprise customers who deploy our agents. - **How do we process your information?** To deliver and improve the Services, communicate with you, for security and fraud prevention, and to comply with law. - **Do we use your data to train AI models?** No. See “AI and automated processing” below. - **In what situations and with which parties do we share personal information?** With service providers under contract, and in the specific situations described below. - **What are your rights?** Depending on where you are located, applicable privacy law may give you rights over your personal information. - **How do you exercise your rights?** Contact [support@rapidflare.ai](mailto:support@rapidflare.ai). We act on requests in accordance with applicable data protection law. ## Our two roles Rapidflare processes personal information in two distinct capacities, and which one applies determines who is responsible for your data. **As a controller.** When you visit our website, contact us, attend our events, or use our Dashboard as a Rapidflare account holder, we decide why and how your information is processed. This notice describes that processing, and we are accountable to you for it. **As a processor.** Our enterprise customers deploy Rapidflare agents on their own websites and support channels. When you interact with one of those agents, the customer is the controller: they decide what the agent does, what data it collects, and how long it is kept, subject to their contract with us. We process that information only on their documented instructions. If you interacted with an agent on another company’s website and want to exercise privacy rights over that conversation, contact that company first. If you contact us instead, we will refer your request to them and support them in responding. ## What information do we collect? ### Personal information you disclose to us We collect personal information you voluntarily provide when you express interest in our products, participate in activities on the Services, or contact us. This may include: - Names - Email addresses - Phone numbers - Company name and job title - Contact or authentication data - Billing addresses **Sensitive information.** We do not collect or process sensitive personal information. All personal information you provide must be true, complete, and accurate, and you must notify us of any changes. ### Information automatically collected Some information is collected automatically when you visit or use our Services. It does not reveal your specific identity but may include: - IP address and approximate location derived from it - Device and browser type, settings, and language - Referring URLs, pages viewed, and time spent - Session identifiers and interaction events, including interactions with an agent widget - Log and diagnostic data about how the Services perform We collect this to maintain the security and operation of our Services and for internal analytics and reporting. Where this information is collected through cookies and similar technologies, see “Cookies and tracking technologies” below. ### Conversation content When you interact with a Rapidflare agent, we process the messages you send, the responses generated, and the context retrieved to produce those responses. Please do not enter personal information into an agent conversation unless it is necessary for your inquiry. ### Information we receive from third parties We receive information about you from: - **Analytics and business-intelligence providers**, which may identify the organization associated with a visit to our website and provide business contact details for people at that organization. - **Our enterprise customers**, when they deploy our agents or supply content and contact data for use in the Services. - **Our service providers**, in the course of delivering services to us. ## How do we process your information? We process your personal information for the following purposes: - **To deliver and operate the Services** you request, including responding to agent conversations and providing Dashboard access. - **To respond to your inquiries** and provide support. - **To send marketing and promotional communications**, where you have consented and subject to your right to opt out at any time. - **To measure and improve the quality and accuracy of the Services**, including reviewing conversations for quality and building evaluation sets. We do not use this content to train AI models, see below. - **To analyze usage** and understand how our Services are used, so we can improve them. - **For security and fraud prevention**, including protecting the Services against abuse. - **To comply with our legal obligations** and to establish, exercise, or defend legal claims. - **To save or protect an individual’s vital interest**, such as to prevent harm. ## AI and automated processing Our Services use generative AI to produce responses. Two commitments govern how we handle your data in that context: **We do not use your content to train our models.** Content you provide to, or receive from, the Services is not used to train, fine-tune, or otherwise adjust the weights of any machine learning model, and we do not provide it to model providers for training. **We do review content for quality.** We investigate low-rated responses and build evaluation sets used to measure and improve accuracy. This does not modify any model. Evaluation records derived from a customer’s conversations are deleted on the same schedule as that customer’s other data. Our agents generate responses automatically, but we do not use automated decision-making that produces legal or similarly significant effects concerning you. If you are in the EEA or UK, you have the right not to be subject to such decision-making, described under “What are your privacy rights?” below. ## What legal bases do we rely on? We only process your personal information when we have a valid legal reason to do so. ### If you are located in the EU or UK The GDPR and UK GDPR require us to explain the legal bases we rely on: - **Consent.** Where you have given us permission to use your information for a specific purpose, such as marketing communications or non-essential cookies. You can withdraw your consent at any time. - **Performance of a contract.** Where processing is necessary to provide Services you have requested or to perform our contract with you or your organization. - **Legitimate interests.** Where processing is necessary for our legitimate business interests and those interests are not overridden by your rights, for example, to secure our Services, to understand how they are used, and to measure and improve their quality and accuracy. - **Legal obligations.** Where processing is necessary for compliance with our legal obligations. - **Vital interests.** Where processing is necessary to protect your vital interests or those of a third party. ### If you are located in Canada We may process your information if you have given us express consent, or where consent can be inferred (implied consent). You can withdraw your consent at any time. In some exceptional cases, applicable law may permit processing without your consent, including: - Collection that is clearly in the interests of an individual and consent cannot be obtained in a timely way. - Investigations and fraud detection or prevention. - Business transactions, provided certain conditions are met. - Witness statements where collection is necessary to assess, process, or settle an insurance claim. - Identifying injured, ill, or deceased persons and communicating with next of kin. - Reasonable grounds to believe an individual is, was, or may be a victim of financial abuse. - Compromising the availability or accuracy of information if consent were sought, and the collection is reasonable for investigating a breach of agreement or contravention of law. - Compliance with a subpoena, warrant, court order, or production rules. - Information produced by an individual in the course of their employment, business, or profession, where collection is consistent with the purposes for which it was produced. - Collection solely for journalistic, artistic, or literary purposes. - Publicly available information specified by the regulations. ## Cookies and tracking technologies We use cookies and similar technologies on our website for analytics, to understand which organizations visit us, and to measure advertising performance. **Non-essential cookies and tracking scripts do not load until you accept them.** When you first visit our website you are presented with a consent banner. Analytics and advertising technologies, including Google Analytics, the LinkedIn Insight Tag, Apollo, and Mixpanel, are loaded only after you click Accept. Strictly necessary technologies required to operate the site may be set without consent. You can withdraw your consent at any time by clearing the consent cookie in your browser, and you can control cookies through your browser settings. Blocking some cookies may affect how the website functions. ## When and with whom do we share your personal information? We share personal information in the following situations: - **Service providers and sub-processors.** With vendors who perform services for us, hosting, analytics, observability, customer relationship management, and support tooling, under written contracts that restrict them to processing on our instructions. - **Business transfers.** In connection with, or during negotiations of, any merger, sale of company assets, financing, or acquisition. - **Affiliates.** With our affiliates, whom we require to honor this notice. - **Business partners.** With our business partners to offer you certain products, services, or promotions. - **Legal and safety.** Where required to comply with applicable law, a court order, subpoena, or other lawful request, or where necessary to protect the rights, property, or safety of Rapidflare, our customers, or others. We do not sell your personal information. Because our analytics and advertising technologies load only after you accept the consent banner, no information is shared with those providers unless you have consented. ## Our sub-processors We engage the following categories of sub-processor. All are bound by written data processing agreements. - **Cloud infrastructure and hosting**: Google Cloud Platform, Vercel - **AI model providers**: the providers of the underlying language models used to generate responses - **Observability and quality monitoring**: LangSmith - **Website analytics and marketing**: Google Analytics, LinkedIn, Apollo, Mixpanel - **Customer relationship management**: HubSpot - **Support and issue tracking**: Linear We do not transmit EU or UK personal data to any third party or vendor until an appropriate data processing agreement has been executed. ## International transfers Our Services are hosted in the United States, and we and our sub-processors may process your information there and in other countries. If you access the Services from outside the United States, your information may be transferred to, stored, and processed in a country whose data protection laws differ from those in your jurisdiction. Where we transfer personal data out of the EEA or UK, we do so under appropriate safeguards, including standard contractual clauses. ## How long do we keep your information? We keep your information only as long as necessary for the purposes described in this notice, unless a longer retention period is required or permitted by law. **Data processed on behalf of our customers.** Where we act as a processor, customer data, including conversation transcripts, session and interaction telemetry, contact details captured through the Services, ingested content, derived artifacts such as embeddings and vector indices, observability traces, feedback records, and evaluation sets, is deleted within sixty (60) days of the end of that customer’s contract, unless legal or regulatory requirements dictate otherwise. **Aggregated and business records.** Aggregated usage metrics that contain no message content and identify no individual, and ordinary business records such as billing records, support tickets, and sales records, are retained beyond that period as records of our business relationship. **Personal information generally.** Personally identifiable information is deleted or de-identified as soon as it no longer has a business use, and in response to a verified request where we have no legitimate business interest or legal obligation to retain it. When we have no ongoing legitimate business need to process your personal information, we will delete or anonymize it, or, if that is not possible because the information is stored in backup archives, we will securely store it and isolate it from further processing until deletion is possible. ## How do we keep your information safe? We implement appropriate technical and organizational measures to protect your personal information, including encryption of personal data at rest and in transit, access restricted on a need-to-know basis, and vendor security assessment before we share data with third parties. No system is entirely secure, and we cannot guarantee absolute security. If we become aware of a personal data breach affecting your information, we will notify affected parties and, where we act as a processor, the relevant customer, in accordance with applicable law and our incident response procedures. ## Do we collect information from minors? We do not knowingly collect data from or market to children under 18 years of age. By using the Services, you represent that you are at least 18 or that you are the parent or guardian of such a minor and consent to that minor’s use of the Services. If we learn that personal information from users under 18 has been collected, we will deactivate the account and take reasonable measures to promptly delete such data. If you become aware of any data we may have collected from children under 18, contact [support@rapidflare.ai](mailto:support@rapidflare.ai). ## What are your privacy rights? In some regions, including the EEA, UK, Switzerland, and Canada, you have rights under applicable data protection law. These may include the right to: 1. Request access to and obtain a copy of your personal information. 2. Request rectification or erasure. 3. Restrict the processing of your personal information. 4. Data portability, where applicable. Where we receive a portability request, we will export the data in a commonly used industry-standard format and make it available for download by you. 5. Not be subject to automated decision-making, including profiling. In certain circumstances you may also object to processing. To make a request, contact us using the details under “How can you contact us about this notice?” below. We will acknowledge your request within three (3) business days and respond within twenty-five (25) days. Where a request is complex or numerous, we may extend that period as permitted by applicable law and will tell you if we do. If you are located in the EEA or UK and believe we are unlawfully processing your personal information, you have the right to complain to your Member State data protection authority or the UK Information Commissioner’s Office. If you are located in Switzerland, you may contact the Federal Data Protection and Information Commissioner. ### Our EU and UK representative Rapidflare has appointed a representative under Article 27 of the GDPR and UK GDPR as a contact point for data subjects and supervisory authorities: Andreas Lambauer [andreas@rapidflare.ai](mailto:andreas@rapidflare.ai) Germany ### Withdrawing your consent Where we rely on your consent, which may be express or implied depending on applicable law, you have the right to withdraw it at any time. Withdrawal will not affect the lawfulness of processing before its withdrawal, nor processing conducted on other lawful grounds where permitted. To opt out of marketing communications, use the unsubscribe link in any message or email [support@rapidflare.ai](mailto:support@rapidflare.ai). You may still receive service-related communications necessary for administration and use of your account. ## Controls for Do-Not-Track features Most web browsers and some mobile operating systems include a Do-Not-Track (“DNT”) feature you can activate to signal your preference not to have data about your online browsing activities monitored and collected. No uniform DNT standard has been finalized, so we do not currently respond to DNT signals. Our consent banner gives you direct control over non-essential tracking on our website. If a DNT standard is adopted that we must follow, we will update this notice. ## Compelled disclosure We may receive legal demands for information, such as court orders, search warrants, subpoenas, and government investigations. On receipt, we notify our legal counsel and investigate the demand. Where we determine a demand is valid, we disclose only the information specifically demanded that we are reasonably able to locate. We do not act on overly broad or vague demands. Where we are permitted to do so, we will notify the affected customer before disclosing their information, though in some cases we may be legally prohibited from giving notice. ## Do United States residents have specific privacy rights? If you are a resident of California, Colorado, Connecticut, Utah, or Virginia, you have specific rights regarding your personal information. ### Categories we disclose to service providers We disclose the following categories of personal information to service providers for business purposes, under written contract: identifiers (such as name, email address, and IP address), commercial information, internet and network activity information, and the contents of communications you direct to us or to an agent. We do not sell personal information, and we do not share personal information for cross-context behavioral advertising except where you have consented through our cookie banner. You can withdraw that consent at any time. We may use your personal information for our own business purposes, such as internal research for technological development and demonstration. This is not considered “selling” of personal information. ## California residents California Civil Code Section 1798.83, the “Shine The Light” law, permits California residents to request, once a year and free of charge, information about categories of personal information (if any) we disclosed to third parties for direct marketing purposes, and the names and addresses of all third parties with which we shared personal information in the preceding calendar year. If you are under 18 years of age, reside in California, and have a registered account with the Services, you have the right to request removal of unwanted data that you publicly post. Contact us using the information below and include the email address associated with your account and a statement that you reside in California. Note that data may not be completely removed from all our systems, such as backups. ### CCPA privacy notice This section applies only to California residents. Under the California Consumer Privacy Act (CCPA), you have the rights listed below. The California Code of Regulations defines a “resident” as: 1. Every individual who is in the State of California for other than a temporary or transitory purpose, and 2. Every individual who is domiciled in the State of California who is outside the State of California for a temporary or transitory purpose. All other individuals are defined as “non-residents.” ### Your rights with respect to your personal data **Right to request deletion of the data: Request to delete.** You can ask for the deletion of your personal information. We will respect your request and delete it, subject to certain exceptions provided by law. **Right to be informed: Request to know.** Depending on the circumstances, you have a right to know: - Whether we collect and use your personal information. - The categories of personal information that we collect. - The purposes for which the collected personal information is used. - Whether we sell or share personal information with third parties. - The categories of personal information that we sold, shared, or disclosed for a business purpose. - The categories of third parties to whom personal information was sold, shared, or disclosed for a business purpose. - The business or commercial purpose for collecting, selling, or sharing personal information. - The specific pieces of personal information we collected about you. In accordance with applicable law, we are not obligated to provide or delete consumer information that is de-identified, or to re-identify individual data to verify a consumer request. **Right to non-discrimination for the exercise of a consumer’s privacy rights.** We will not discriminate against you if you exercise your privacy rights. **Right to limit use and disclosure of sensitive personal information.** We do not process consumer sensitive personal information. ### Verification process Upon receiving your request, we will verify your identity to determine that you are the same person about whom we have information in our system. These efforts may require us to ask you to provide information we can match against information you previously provided. We may also contact you through a communication method you previously provided. We will only use personal information provided in your request to verify your identity or authority to make the request, and we will delete any additionally provided information as soon as we finish verifying you. ### Other privacy rights - You may object to the processing of your personal information. - You may request correction of your personal data if it is incorrect or no longer relevant, or ask to restrict processing. - You can designate an authorized agent to make a request under the CCPA on your behalf. We may deny a request from an authorized agent that does not submit proof of authorization. - You may request to opt out from future selling or sharing of your personal information to third parties. Upon receiving an opt-out request, we will act on it as soon as feasibly possible, but no later than fifteen (15) days from the date of the request. To exercise these rights, contact us at [support@rapidflare.ai](mailto:support@rapidflare.ai). ## Colorado residents This section applies only to Colorado residents. Under the Colorado Privacy Act (CPA), you have the rights listed below. These rights are not absolute, and in certain cases we may decline your request as permitted by law. - Right to be informed whether or not we are processing your personal data. - Right to access your personal data. - Right to correct inaccuracies in your personal data. - Right to request deletion of your personal data. - Right to obtain a copy of the personal data you previously shared with us. - Right to opt out of the processing of your personal data if it is used for targeted advertising, the sale of personal data, or profiling. To exercise these rights, email [support@rapidflare.ai](mailto:support@rapidflare.ai). If we decline to take action and you wish to appeal, email us at the same address. Within forty-five (45) days of receipt of an appeal, we will inform you in writing of any action taken or not taken, with a written explanation. ## Connecticut residents This section applies only to Connecticut residents. Under the Connecticut Data Privacy Act (CTDPA), you have the rights listed below. These rights are not absolute. - Right to be informed whether or not we are processing your personal data. - Right to access your personal data. - Right to correct inaccuracies in your personal data. - Right to request deletion of your personal data. - Right to obtain a copy of the personal data you previously shared with us. - Right to opt out of the processing of your personal data if it is used for targeted advertising, the sale of personal data, or profiling. To exercise these rights, email [support@rapidflare.ai](mailto:support@rapidflare.ai). If we decline and you wish to appeal, email us at the same address. Within sixty (60) days of receipt of an appeal, we will inform you in writing of any action taken or not taken, with a written explanation. ## Utah residents This section applies only to Utah residents. Under the Utah Consumer Privacy Act (UCPA), you have the rights listed below. These rights are not absolute. - Right to be informed whether or not we are processing your personal data. - Right to access your personal data. - Right to request deletion of your personal data. - Right to obtain a copy of the personal data you previously shared with us. - Right to opt out of the processing of your personal data if it is used for targeted advertising or the sale of personal data. To exercise these rights, email [support@rapidflare.ai](mailto:support@rapidflare.ai). ## Virginia residents Under the Virginia Consumer Data Protection Act (VCDPA): - **“Consumer”** means a natural person who is a resident of the Commonwealth acting only in an individual or household context. It does not include a natural person acting in a commercial or employment context. - **“Personal data”** means any information that is linked or reasonably linkable to an identified or identifiable natural person. It does not include de-identified data or publicly available information. - **“Sale of personal data”** means the exchange of personal data for monetary consideration. ### Your rights with respect to your personal data - Right to be informed whether or not we are processing your personal data. - Right to access your personal data. - Right to correct inaccuracies in your personal data. - Right to request deletion of your personal data. - Right to obtain a copy of the personal data you previously shared with us. - Right to opt out of the processing of your personal data if it is used for targeted advertising, the sale of personal data, or profiling. ### Exercising your rights Email us at [support@rapidflare.ai](mailto:support@rapidflare.ai). If you are using an authorized agent, we may deny a request that does not include proof of authorization. ### Verification process We may request additional information reasonably necessary to verify you and your consumer’s request. If the request is submitted through an authorized agent, we may need additional information to verify your identity. We will respond without undue delay, but within forty-five (45) days of receipt. The response period may be extended once by forty-five (45) additional days when reasonably necessary. We will inform you of any such extension within the initial period. ### Right to appeal If we decline to take action, we will inform you of our decision and reasoning. To appeal, email [support@rapidflare.ai](mailto:support@rapidflare.ai). Within sixty (60) days of receipt of an appeal, we will inform you in writing of any action taken or not taken, with a written explanation. If your appeal is denied, you may contact the Attorney General to submit a complaint. ## Do we make updates to this notice? Yes, we will update this notice as necessary to stay compliant with relevant laws. The updated version will be indicated by an updated “Last revised” date and will be effective as soon as it is accessible. If we make material changes, we may notify you either by prominently posting a notice or by directly sending you a notification. We encourage you to review this notice frequently. ## How can you contact us about this notice? If you have questions or comments about this notice, email us at [support@rapidflare.ai](mailto:support@rapidflare.ai) or contact us by post at: Rapidflare, Inc. 325 S 1st St #120 San Jose, CA 95113 United States Data subjects in the EEA or UK may also contact our Article 27 representative, whose details appear under “What are your privacy rights?” above. ## How can you review, update, or delete the data we collect from you? Based on the applicable laws of your country, you may have the right to request access to the personal information we collect, change it, or delete it. To request to review, update, or delete your personal information, email [support@rapidflare.ai](mailto:support@rapidflare.ai). --- # Terms of Service Source: https://www.rapidflare.ai/terms > The terms that govern use of the Rapidflare website and services when no negotiated agreement applies. Legal # Terms of Service Last revised July 31, 2026 These Terms of Service (the “Terms”) are a legally binding agreement between you, whether personally or on behalf of an entity (“you”), and **Rapidflare, Inc.** (“Rapidflare,” “we,” “us,” or “our”), a company registered in Delaware, United States. They govern your access to and use of our website at [https://www.rapidflare.ai](https://www.rapidflare.ai) (the “Site”), the Rapidflare Dashboard at [https://dashboard.rapidflare.ai](https://dashboard.rapidflare.ai) (the “Dashboard”), the Rapidflare AI agents and copilots we make available (the “Agents”), and any other related products and services that link to these Terms (collectively, the “Services”). Rapidflare provides an AI platform for technical sales, product selection, and customer support. By accessing or using the Services, you confirm that you have read, understood, and agree to be bound by these Terms. **If you do not agree with these Terms, you are not permitted to use the Services and must discontinue use immediately.** The Services are intended for users who are at least 18 years old. Persons under the age of 18 are not permitted to use or register for the Services. ## Relationship to negotiated agreements **Most Rapidflare customers are covered by a separately negotiated contract, and that contract, not this page, governs their relationship with us.** If you have entered into a separate written agreement with Rapidflare, including a Cloud Services Agreement, Master Services Agreement, Order Form, Statement of Work, Data Processing Agreement, or similar enterprise agreement (each, a “Negotiated Agreement”), then: - The Negotiated Agreement governs your access to and use of the Services. - These Terms apply only to the extent they address matters your Negotiated Agreement does not. - **In the event of any conflict or inconsistency between these Terms and a Negotiated Agreement, the Negotiated Agreement controls.** This means a Negotiated Agreement supersedes these Terms with respect to any subject it covers, including fees and payment, subscription term and renewal, cancellation and refunds, service levels and support, use and volume limits, warranties, limitations of liability, indemnification, intellectual property, confidentiality, data processing and retention, and governing law and venue. These Terms apply in full to anyone who uses the Services without a Negotiated Agreement, including visitors to the Site, evaluation and trial users, and users of publicly accessible Agents. Where Rapidflare Agents are made available to you through a third party’s website, application, or support channel, your use may also be subject to that third party’s own terms. Rapidflare is not responsible for those terms, and nothing here creates obligations on our part to you beyond the Services we provide. ## Our services The information provided when using the Services is not intended for distribution to or use by any person or entity in any jurisdiction or country where such distribution or use would be contrary to law or regulation, or which would subject us to any registration requirement within such jurisdiction or country. Those who choose to access the Services from other locations do so on their own initiative and are solely responsible for compliance with local laws. Except where expressly agreed in a Negotiated Agreement, the Services are not tailored to comply with industry-specific regulations such as the Health Insurance Portability and Accountability Act (HIPAA), the Federal Information Security Management Act (FISMA), or the Gramm-Leach-Bliley Act (GLBA). If your use would be subject to such laws, do not use the Services without a written agreement addressing them. We reserve the right to change, modify, or remove the contents of the Services at any time and at our sole discretion. We have no obligation to update any information on the Services. ## Intellectual property rights ### Our intellectual property We are the owner or licensee of all intellectual property rights in our Services, including all source code, databases, functionality, software, website designs, audio, video, text, photographs, and graphics (collectively, the “Content”), as well as the trademarks, service marks, and logos contained therein (the “Marks”). Our Content and Marks are protected by copyright, trademark, and other intellectual property laws in the United States and around the world. The Content and Marks are provided in or through the Services “AS IS” for your internal business purpose only. ### Your use of our services Subject to your compliance with these Terms, we grant you a non-exclusive, non-transferable, revocable license to access the Services and to download or print a copy of any portion of the Content to which you have properly gained access, solely for your internal business purpose. Except as set out in this section or elsewhere in these Terms, no part of the Services and no Content or Marks may be copied, reproduced, aggregated, republished, uploaded, posted, publicly displayed, encoded, translated, transmitted, distributed, sold, licensed, or otherwise exploited for any commercial purpose without our express prior written permission. If you wish to make any other use of the Services, Content, or Marks, address your request to [support@rapidflare.ai](mailto:support@rapidflare.ai). If we grant permission to post, reproduce, or publicly display any part of our Services or Content, you must identify us as the owner or licensor and ensure that any copyright or proprietary notice remains visible. We reserve all rights not expressly granted to you in and to the Services, Content, and Marks. Any breach of this section constitutes a material breach of these Terms and your right to use the Services will terminate immediately. ### Your submissions By sending us any question, comment, suggestion, idea, or feedback about the Services (“Submissions”), you agree that we may use and share such feedback for any purpose without compensation to you. This section does not apply to Content you provide to or receive from the Services, which is addressed under “Your content and AI output” below. You warrant that your Submissions are original to you or that you have the necessary rights to provide them, that they do not constitute confidential information, and that they are not illegal, harassing, hateful, defamatory, obscene, abusive, discriminatory, false, or misleading. ## User representations By using the Services, you represent and warrant that: (1) you have the legal capacity to agree to and comply with these Terms; (2) you are not a minor in the jurisdiction in which you reside; (3) you will not access the Services through automated or non-human means except as we expressly permit; (4) you will not use the Services for any illegal or unauthorized purpose; and (5) your use of the Services will not violate any applicable law or regulation. If you provide any information that is untrue, inaccurate, not current, or incomplete, we have the right to suspend or terminate your account and refuse any current or future use of the Services. ## Accounts and access You are responsible for maintaining the confidentiality of your account credentials and for all activity that occurs under your account. You agree to notify us immediately at [support@rapidflare.ai](mailto:support@rapidflare.ai) of any unauthorized use of your account or any other breach of security. You may not share credentials with, or permit access by, anyone outside your organization, or otherwise make the Services available to multiple users in a manner that circumvents agreed user or volume limits. ## Fees and payment Fees, payment methods, billing cycles, invoicing, and applicable taxes are set out in your Negotiated Agreement or applicable Order Form. Where no Negotiated Agreement or Order Form applies, the Services are made available at no charge and we may modify or discontinue that availability at any time. Where fees do apply, you agree to provide current, complete, and accurate billing and account information, and to update it promptly. Sales and other applicable taxes will be added where required. All payments are in US dollars unless otherwise agreed in writing. ## Subscription and cancellation Subscription term, renewal, cancellation, and any refund rights are governed by your Negotiated Agreement or Order Form. Where no such agreement applies, we may suspend or discontinue your access to the Services at any time. To cancel a subscription or discuss your agreement, contact [support@rapidflare.ai](mailto:support@rapidflare.ai). ## Prohibited activities You may not access or use the Services for any purpose other than that for which we make the Services available. As a user of the Services, you agree not to: - Systematically retrieve data or other content from the Services to create or compile, directly or indirectly, a collection, compilation, database, or directory, without written permission from us. - Trick, defraud, or mislead us or other users, especially in any attempt to learn sensitive account information such as passwords. - Circumvent, disable, or otherwise interfere with security-related features of the Services, including features that enforce limitations on use of the Services or the Content. - Use any information obtained from the Services to harass, abuse, or harm another person, or to harass, intimidate, or threaten our employees or agents. - Make improper use of our support services or submit false reports of abuse or misconduct. - Use the Services in a manner inconsistent with any applicable law or regulation. - Engage in unauthorized framing of, or linking to, the Services. - Upload or transmit, or attempt to upload or transmit, viruses, Trojan horses, or other material that interferes with any party’s use of the Services, or that modifies, impairs, disrupts, or interferes with the use, features, functions, operation, or maintenance of the Services. - Engage in any automated use of the system, such as using scripts to send messages, or using any data mining, robots, scrapers, or similar data gathering and extraction tools, except through interfaces we expressly provide for that purpose. - Delete any copyright or other proprietary rights notice from any Content. - Attempt to impersonate another user or person, or use the account of another user. - Interfere with, disrupt, or create an undue burden on the Services or the networks or services connected to the Services. - Attempt to bypass any measures of the Services designed to prevent or restrict access. - Copy or adapt the Services’ software, or, except as permitted by applicable law, decipher, decompile, disassemble, or reverse engineer any software comprising any part of the Services. - Use the Services to develop, train, or improve any product, service, or model that is directly or indirectly competitive with the Services, or to benchmark the Services for publication without our written consent. - Make any unauthorized use of the Services, including collecting usernames or email addresses of users for the purpose of sending unsolicited email, or creating accounts by automated means or under false pretenses. Any use of the Services in violation of the foregoing violates these Terms and may result in termination or suspension of your rights to use the Services. ## Your content and AI output You may provide input to the Services (“Input”) and receive output from the Services based on that Input (“Output”). Input and Output are collectively “Content.” You are responsible for Content, including ensuring that it does not violate any applicable law or these Terms. You represent and warrant that you have all rights, licenses, and permissions needed to provide Input to the Services. **Ownership.** As between you and Rapidflare, and to the extent permitted by applicable law, you retain your ownership rights in Input and you own the Output. We assign to you all our right, title, and interest, if any, in and to Output. **Similarity of content.** Due to the nature of the Services and of artificial intelligence generally, Output may not be unique and other users may receive similar output. Our assignment above does not extend to other users’ output or to any third-party output. **Our use of content.** We may use Content to provide, maintain, support, develop, and improve the Services, to comply with applicable law, to enforce our terms and policies, and to keep the Services safe. This includes reviewing conversations for quality, for example, investigating low-rated answers and building evaluation sets used to measure and improve the accuracy of the Services. **Training.** We do not use your Content to train our models. Content is not used to train, fine-tune, or otherwise adjust the weights of any machine learning model, and we do not provide it to model providers for training. Quality evaluation as described above does not modify any model and is not training. **Accuracy.** When you use the Services you understand and agree that: - Output may not always be accurate. You should not rely on Output as a sole source of truth or factual information, or as a substitute for professional advice. - You are responsible for evaluating Output for accuracy and appropriateness for your use case, including human review as appropriate, before using or sharing it. - You must not use any Output relating to a person for any purpose that could have a legal or material impact on that person, such as decisions about credit, education, employment, housing, insurance, legal matters, or medical care. - The Services may produce incomplete, incorrect, or objectionable Output that does not represent Rapidflare’s views. If Output references any third-party product or service, that does not mean the third party endorses or is affiliated with Rapidflare. ## Data usage and retention **Purpose.** Data provided by a customer is used for the sole purpose of delivering the Services. **Non-training assurance.** We will not use customer proprietary data to train or fine-tune any machine learning or artificial intelligence model. Customer data is used to deliver the agreed Services and to measure and improve the quality of the Services, as described under “Your content and AI output” above. **Retention and deletion.** We retain customer data only for as long as necessary to deliver the contracted Services. Following contract termination, customer data is deleted from our systems within sixty (60) days, unless legal or regulatory requirements dictate otherwise. The customer retains ownership of their data. Data deleted on this schedule includes conversation transcripts and messages, session and interaction telemetry, end-user contact details captured through the Services, content supplied to us for ingestion, artifacts derived from that content such as embeddings and vector indices, observability traces held by our processors, feedback and quality records, and evaluation sets derived from your conversations. Evaluation sets are never used for training, and are never shared with or used to serve another customer. Two categories are retained beyond that period. First, aggregated usage metrics and counts that contain no message content and identify no individual. Second, ordinary business records, billing and usage logs, support tickets, and sales records, which we keep as records of our business relationship rather than as part of the Services. Personally identifiable information is deleted or de-identified as soon as it no longer has a business use, and in response to a verified request from a data subject where we have no legitimate business interest or legal obligation to retain it. **Security.** We implement reasonable technical and organizational measures to safeguard the confidentiality and integrity of customer data. You acknowledge that no data transmission or storage system is entirely secure, and we cannot guarantee absolute security. Where a Negotiated Agreement or Data Processing Agreement addresses these matters, that agreement controls. ## Client applications If you access the Agents through a Rapidflare client application, we grant you a revocable, non-exclusive, non-transferable, limited right to install and use that application on devices owned or controlled by you, strictly in accordance with these Terms. You shall not: (1) except as permitted by applicable law, decompile, reverse engineer, disassemble, attempt to derive the source code of, or decrypt the application; (2) make any modification, adaptation, improvement, enhancement, translation, or derivative work from the application; (3) violate any applicable law in connection with your use of the application; (4) remove, alter, or obscure any proprietary notice posted by us or our licensors; (5) make the application available over a network or other environment permitting access by multiple devices or users at the same time beyond your agreed limits; (6) use the application to create a product, service, or software that is directly or indirectly competitive with or a substitute for the Services; or (7) use the application to send automated queries to any website or to send unsolicited commercial email. ## Services management We reserve the right, but not the obligation, to: (1) monitor the Services for violations of these Terms; (2) take appropriate legal action against anyone who, in our sole discretion, violates the law or these Terms, including reporting such user to law enforcement authorities; (3) refuse, restrict access to, or limit the availability of any of your Content or any portion of it, to the extent technologically feasible; (4) remove from the Services or disable files and content that are excessive in size or otherwise burdensome to our systems; and (5) otherwise manage the Services in a manner designed to protect our rights and property and to facilitate proper functioning of the Services. ## Privacy We care about data privacy and security. Please review our [Privacy Policy](https://www.rapidflare.ai/privacy). By using the Services, you agree to be bound by our Privacy Policy, which is incorporated into these Terms. The Services are hosted in the United States. If you access the Services from a region with laws governing personal data collection, use, or disclosure that differ from those of the United States, then through your continued use of the Services you are transferring your data to the United States and consent to it being processed there. ## Term and termination These Terms remain in full force and effect while you use the Services. Without limiting any other provision of these Terms, and subject to any Negotiated Agreement, we reserve the right, in our sole discretion and without notice or liability, to deny access to and use of the Services, including by blocking certain IP addresses, to any person for any reason, including for breach of any representation, warranty, or covenant in these Terms or of any applicable law or regulation. We may terminate your use of or participation in the Services, or delete any content or information you posted, at any time and in our sole discretion. If we terminate or suspend your account, you are prohibited from registering and creating a new account under your name, a fake or borrowed name, or the name of any third party. In addition to terminating or suspending your account, we reserve the right to take appropriate legal action, including pursuing civil, criminal, and injunctive redress. ## Modifications and interruptions We reserve the right to change, revise, update, suspend, discontinue, or otherwise modify the Services at any time and for any reason without notice to you. We will not be liable to you or any third party for any modification, price change, suspension, or discontinuance of the Services. We cannot guarantee that the Services will be available at all times. We may experience hardware, software, or other problems, or need to perform maintenance, resulting in interruptions, delays, or errors. Except as set out in a Negotiated Agreement, you agree that we have no liability for any loss, damage, or inconvenience caused by your inability to access or use the Services during any downtime or discontinuance. Nothing in these Terms obligates us to maintain and support the Services or to supply any corrections, updates, or releases. Where a Negotiated Agreement includes a service level commitment, that commitment governs. ## Corrections There may be information on the Services that contains typographical errors, inaccuracies, or omissions, including descriptions, pricing, and availability. We reserve the right to correct any errors, inaccuracies, or omissions and to change or update the information on the Services at any time, without prior notice. ## Disclaimer THE SERVICES ARE PROVIDED ON AN AS-IS AND AS-AVAILABLE BASIS. YOU AGREE THAT YOUR USE OF THE SERVICES WILL BE AT YOUR SOLE RISK. TO THE FULLEST EXTENT PERMITTED BY LAW, WE DISCLAIM ALL WARRANTIES, EXPRESS OR IMPLIED, IN CONNECTION WITH THE SERVICES AND YOUR USE THEREOF, INCLUDING THE IMPLIED WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE, AND NON-INFRINGEMENT. WE MAKE NO WARRANTIES OR REPRESENTATIONS ABOUT THE ACCURACY OR COMPLETENESS OF THE SERVICES’ CONTENT OR THE CONTENT OF ANY WEBSITES OR APPLICATIONS LINKED TO THE SERVICES, AND WE ASSUME NO LIABILITY OR RESPONSIBILITY FOR ANY (1) ERRORS, MISTAKES, OR INACCURACIES OF CONTENT AND MATERIALS, (2) PERSONAL INJURY OR PROPERTY DAMAGE RESULTING FROM YOUR ACCESS TO AND USE OF THE SERVICES, (3) ANY UNAUTHORIZED ACCESS TO OR USE OF OUR SECURE SERVERS AND ANY PERSONAL OR FINANCIAL INFORMATION STORED THEREIN, (4) ANY INTERRUPTION OR CESSATION OF TRANSMISSION TO OR FROM THE SERVICES, (5) ANY BUGS, VIRUSES, TROJAN HORSES, OR THE LIKE WHICH MAY BE TRANSMITTED TO OR THROUGH THE SERVICES BY ANY THIRD PARTY, OR (6) ANY ERRORS OR OMISSIONS IN ANY CONTENT AND MATERIALS OR FOR ANY LOSS OR DAMAGE OF ANY KIND INCURRED AS A RESULT OF THE USE OF ANY CONTENT POSTED, TRANSMITTED, OR OTHERWISE MADE AVAILABLE VIA THE SERVICES. ## Limitation of liability IN NO EVENT WILL WE OR OUR DIRECTORS, EMPLOYEES, OR AGENTS BE LIABLE TO YOU OR ANY THIRD PARTY FOR ANY DIRECT, INDIRECT, CONSEQUENTIAL, EXEMPLARY, INCIDENTAL, SPECIAL, OR PUNITIVE DAMAGES, INCLUDING LOST PROFIT, LOST REVENUE, LOSS OF DATA, OR OTHER DAMAGES ARISING FROM YOUR USE OF THE SERVICES, EVEN IF WE HAVE BEEN ADVISED OF THE POSSIBILITY OF SUCH DAMAGES. NOTWITHSTANDING ANYTHING TO THE CONTRARY CONTAINED HEREIN, OUR LIABILITY TO YOU FOR ANY CAUSE WHATSOEVER AND REGARDLESS OF THE FORM OF THE ACTION WILL AT ALL TIMES BE LIMITED TO THE AMOUNT PAID, IF ANY, BY YOU TO US DURING THE SIX (6) MONTH PERIOD PRIOR TO THE CAUSE OF ACTION ARISING. CERTAIN US STATE LAWS AND INTERNATIONAL LAWS DO NOT ALLOW LIMITATIONS ON IMPLIED WARRANTIES OR THE EXCLUSION OR LIMITATION OF CERTAIN DAMAGES. IF THESE LAWS APPLY TO YOU, SOME OR ALL OF THE ABOVE DISCLAIMERS OR LIMITATIONS MAY NOT APPLY, AND YOU MAY HAVE ADDITIONAL RIGHTS. Where a Negotiated Agreement sets out a different limitation of liability, that limitation governs. ## Indemnification You agree to defend, indemnify, and hold us harmless, including our subsidiaries, affiliates, and all of our respective officers, agents, partners, and employees, from and against any loss, damage, liability, claim, or demand, including reasonable attorneys’ fees and expenses, made by any third party arising out of: (1) your use of the Services; (2) your breach of these Terms; (3) any breach of your representations and warranties set forth in these Terms; (4) your violation of the rights of a third party, including intellectual property rights; or (5) any overt harmful act toward any other user of the Services with whom you connected via the Services. Notwithstanding the foregoing, we reserve the right, at your expense, to assume the exclusive defense and control of any matter for which you are required to indemnify us, and you agree to cooperate, at your expense, with our defense of such claims. We will use reasonable efforts to notify you of any such claim, action, or proceeding upon becoming aware of it. ## Governing law and dispute resolution These Terms and your use of the Services are governed by and construed in accordance with the laws of the State of Delaware, without regard to its conflict of law principles. Any legal action of whatever nature brought by either you or us shall be commenced exclusively in the state or federal courts located in New Castle County, Delaware, and both parties consent to that jurisdiction and waive all defenses of lack of personal jurisdiction and forum non conveniens with respect to venue and jurisdiction in those courts. Application of the United Nations Convention on Contracts for the International Sale of Goods and the Uniform Computer Information Transaction Act (UCITA) are excluded from these Terms. In no event shall any claim, action, or proceeding related in any way to the Services be commenced more than one (1) year after the cause of action arose. Where a Negotiated Agreement specifies a different governing law or venue, that agreement controls. ## Electronic communications, transactions, and signatures Visiting the Services, sending us emails, and completing online forms constitute electronic communications. You consent to receive electronic communications, and you agree that all agreements, notices, disclosures, and other communications we provide to you electronically satisfy any legal requirement that such communication be in writing. YOU HEREBY AGREE TO THE USE OF ELECTRONIC SIGNATURES, CONTRACTS, ORDERS, AND OTHER RECORDS, AND TO ELECTRONIC DELIVERY OF NOTICES, POLICIES, AND RECORDS OF TRANSACTIONS INITIATED OR COMPLETED BY US OR VIA THE SERVICES. You waive any rights or requirements under any laws in any jurisdiction which require an original signature, or delivery or retention of non-electronic records. ## California users and residents If any complaint with us is not satisfactorily resolved, you can contact the Complaint Assistance Unit of the Division of Consumer Services of the California Department of Consumer Affairs in writing at 1625 North Market Blvd., Suite N 112, Sacramento, California 95834, or by telephone at (800) 952-5210 or (916) 445-1254. ## Do we make updates to these terms? Yes. We reserve the right, in our sole discretion, to make changes or modifications to these Terms at any time. We will indicate changes by updating the “Last revised” date at the top of this page, and the revised Terms are effective as soon as they are accessible. It is your responsibility to review these Terms periodically. Your continued use of the Services after revised Terms are posted means you accept them. Supplemental terms and conditions or documents that may be posted on the Services from time to time are expressly incorporated into these Terms by reference. ## Miscellaneous These Terms, together with any policies or operating rules we post on the Services, constitute the entire agreement between you and us **except where a Negotiated Agreement applies, in which case that agreement and these Terms together constitute the entire agreement, and the Negotiated Agreement controls in the event of conflict.** Our failure to exercise or enforce any right or provision of these Terms does not operate as a waiver of that right or provision. These Terms operate to the fullest extent permissible by law. We may assign any or all of our rights and obligations to others at any time. We are not responsible or liable for any loss, damage, delay, or failure to act caused by any cause beyond our reasonable control. If any provision or part of a provision of these Terms is determined to be unlawful, void, or unenforceable, that provision or part is deemed severable and does not affect the validity and enforceability of the remaining provisions. No joint venture, partnership, employment, or agency relationship is created between you and us as a result of these Terms or your use of the Services. You agree that these Terms will not be construed against us by virtue of our having drafted them. ## How can you contact us about these terms? To resolve a complaint regarding the Services, or to receive further information regarding use of the Services, email us at [support@rapidflare.ai](mailto:support@rapidflare.ai) or contact us by post at: Rapidflare, Inc. 325 S 1st St #120 San Jose, CA 95113 United States ---