Our agents select the correct parts, compare them to the competition, write proposals, and answer support questions with the greatest accuracy, quality, and efficiency.
Every deal in electronics runs through a technical question, and that question almost always waits in a queue.
The deal goes cold by the time an application engineer gets around to answering the question.
Specialists can answer a technical question, but there aren’t enough of them to cover a catalog this size.
Why now
More SKUs, variants, and documentation per part every quarter.
An FAE or a good Sales Engineer is a mix of engineering and sales talent, which is hard to find.
The technical evaluation is over before anyone picks up a phone.
Accurate on parametric data, which is the bar this industry needs.
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.
The agent doesn’t guess. It asks the clarifying questions a senior application engineer would ask, then narrows thousands of parts to the three that work.
Ask how your part stacks up against theirs. The agent reads both catalogs and builds the side by side, spec by spec, with a source on every row.
Feed it the transcript, the BOM, or the requirement. It returns a priced, specced, customer-ready proposal built from your real catalog.
Deployed in the product, on the portal, or in Slack. It answers from your documentation, and hands off cleanly when it should not answer.
New reps and resellers ask the agent instead of waiting for the quarterly training visit. Analytics show you exactly what they did not understand.
General models improvise when the data runs out. On a parametric spec, improvisation is a wrong part in a customer's hands.
Your datasheets, catalogs, BOMs, and support history, turned into one connected map of your products. Built once, and enriched continuously.
It figures out what’s being asked, plans its steps, and only pulls the knowledge that task needs. Complex inside, simple outside.
Your application engineers validate the data and the agents. Their corrections are permanent, not one-off.
Every claim traces to the document it came from. You can see each step the agent took to get there.
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 methodologyEverything that IT, security, and procurement, etc. will ask for before your team is allowed to use any of it.
Your documentation is isolated, encrypted, and never leaves your tenant. Five levels of Rapid Shield sit between your data and others.
One deployment, many audiences. Each hub gets its own agent and its own sources, without duplicating the knowledge behind it.
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.
Connect any enterprise system, then attach a workflow to any action the agent takes. Quotes, orders, CRM handoff, lead capture.
A forward-deployed engineering team that builds the solution with you, and continuous accuracy evaluations so quality is measured, not assumed.
Nobody has to learn a new tool. The agent shows up in the surface they are already in, answering from the same knowledge graph.
Real deployments, with the numbers attached. Pick the one that looks like you.
AskAlibi runs AI search and a conversational assistant on Alibi’s public website, grounded in specs, compatibility, and cross-reference data against competing camera brands.
askSIA grew from a homepage beta into SIA’s site-wide answer layer across standards, training, research, and events, without giving up the rigor members rely on.
A global access-control leader made its documentation AI-ready first, then rolled the agent out through Slack, the SaaS application, and the partner portal.
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 calculatorAssumes 45 minutes lost per unanswered technical question, and 4.3 weeks per month.
Priced on the size of your catalog and number of people using it. Every plan is scoped with our team to ensure transparency.
One agent, one job. For a team proving the value on a focused slice of the catalog.
The agent shows up where your people already work, and you control what it says.
Many agents, many audiences, wired into the systems that run your business.
We answered the questions that come up on every first call.
We benchmark document extraction at 95% average character 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.
We’ll show you how our agents can work off your parts, documentation, and questions, all in 30 minutes.
