Skip to content
AskVault Docs
Try Free →

Automated RFQ response bot for B2B sales teams

Written by Joseph Russo, Principal Architect, Networks and Tech, AskVault · Reviewed by Allison Chan
Last updated: · 6 min read

The RFQ pain

In a typical mid-market B2B sales motion, a sales rep gets an RFQ (request for quotation) email Friday afternoon. It is a long list of questions. Pricing, specs, security, compliance, integration capabilities, support SLAs, references, past performance. The rep spends the weekend cross-referencing the answers from:

  • The product knowledge base on Confluence or Notion
  • Pricing spreadsheets in Google Drive
  • Security questionnaire answers from a previous deal (also in Google Drive, probably in a folder titled security_questionnaires_OLD/)
  • Marketing case studies on the company website
  • The previous RFP response to a similar customer (deeply buried in CRM history)

By Monday they submit a response that is mostly the previous one with a few new paragraphs, while juggling several other deals. RFQ throughput is the bottleneck on revenue.

What the bot replaces

An AI bot trained on the same five sources drafts the answers as fast as the rep can paste questions in. It is not perfect; the rep still reviews and edits the nuanced bits. But the repetitive part of the response (specs, pricing rules, security baseline, integration matrix) gets first-drafted automatically with citations to the source doc for every claim.

Concretely, the bot does this:

  1. Reads each question in the RFQ. Either you paste them in one by one or upload the RFQ document and the bot extracts the questions.
  2. Retrieves the relevant content from your knowledge base. Product specs, pricing rules, past responses on this same topic.
  3. Drafts an answer. With a "Source" citation pointing to the exact doc + paragraph where the claim came from.
  4. Flags unanswerable questions. If the answer isn't in the knowledge base, the bot says so explicitly instead of inventing one. Those questions go to the human.

The rep's job becomes editorial: review the draft answers, edit the nuanced ones, send. The rep edits instead of retyping.

What to put in the knowledge base

Five sources cover most RFQ surface for a real B2B SaaS:

  • Product specs. Your one-pager, datasheet, technical overview. Whatever document covers "what does this product do, what doesn't it do, what's on the roadmap."
  • Pricing rules. Public pricing page is the floor. Internal pricing playbook (volume discounts, partner pricing, multi-year contracts) goes in alongside it with its source Audience set to internal, which keeps it out of retrieval on public channels. Audience has only two values, public and internal: it is not a per-role or per-team permission model.
  • Security baseline. SOC 2 status, encryption at rest/in transit, data residency options, deletion timelines, sub-processor list. Most enterprise RFQs ask many of the same security questions.
  • Past RFP responses. A folder of completed responses to similar deals. Even if the questions weren't identical, retrieval picks up the right boilerplate per topic.
  • Case studies. Customer testimonials, win stories, named deployments. Useful for "tell us about a similar customer" questions.

Add the sources by upload or import. File uploads work on any plan, and Notion connects on every plan. Google Drive, Confluence and GitHub imports need Business. On a smaller plan, export those documents and upload them as files.

Setup

Concrete steps to a working RFQ bot:

  1. Create a sales-only workspace. Name it "RFQ Assistant" or "Sales Knowledge". Keep it separate from your customer-facing chatbot workspace so internal pricing doesn't leak.
  2. Ingest the five sources. Upload files on any plan, connect Notion on any plan, and use the Confluence and Google Drive imports if you are on Business.
  3. Set sensitive sources to Internal. The internal pricing playbook and past RFPs get Audience internal, which keeps them out of retrieval on public channels. Public-facing case studies stay public.
  4. Configure identity verification. Use your SSO middleware to HMAC-sign the rep's user_id before passing it to the widget. Growth+
  5. Deploy the widget inside your sales-tool UI. Embedded in your CRM, in a Slack channel, or as a standalone hosted page. The Slack channel deployment is the most common, since reps live in Slack anyway.

Indexing time depends on how much content you add. When you complete new RFP responses, upload them or resync the changed pages so the bot stays current. Paid plans can set an automatic re-crawl schedule, but until automatic re-crawl is on for your account a scheduled check may not re-read a changed page, so keep using Resync to be sure (details).

How a typical interaction looks

Rep gets an RFQ Friday afternoon. They paste the first question into the bot:

Customer asks: "What encryption do you use at rest and in transit, and are you SOC 2 Type II certified?"

Bot drafts:

Acme encrypts data at rest with AES-256 on SOC 2 Type II audited storage infrastructure. In transit, all connections use TLS 1.2 or higher (TLS 1.3 when the client supports it; no SSLv3 or TLS 1.0/1.1 supported). The application layer is undergoing its own SOC 2 Type II audit; infrastructure controls are already certified.

Sources:

Rep checks the citations, confirms the wording matches what they want to send to a regulated-industry customer, edits one phrase, copies it into the RFQ, and moves to the next question.

Choosing the right plan

Pick a plan by the size of your sales team and how much content you have.

  • Solo founder or 1-2 sales reps, light content (under 50 documents). Starter at $39/mo. 2 workspaces, 2,000 messages. Add your documents as file uploads.
  • 3-10 sales reps, real content library (50 to 200 documents). Growth at $99/mo. Up to 5 workspaces, 6,000 messages, brand-free widget, full identity verification.
  • 10+ sales reps, regulated industry, large RFP archive (200+ documents, 100 MB+ content). Business at $249/mo. 15 workspaces, 15,000 messages, 100 MB cap. Adds the Google Drive, Confluence and GitHub imports.
  • Enterprise sales team facing a procurement security review. Enterprise tier with a signed DPA, quoted by sales. Single sign-on is not yet available on any plan, so talk to sales first if SAML is a hard procurement requirement.

Most B2B SaaS teams start on Growth.

Skills to enable

Four skills are particularly useful for an RFQ workflow:

  • knowledge_search. Default RAG retrieval. Always on.
  • collect_lead. If the bot is also embedded on your marketing site, captures prospect contact info from buying-signal conversations.
  • sdr_lead_qualifier. Records company size, buying stage and budget band, and creates a HubSpot contact. Useful when the bot is in the sales funnel before the RFQ stage. Growth+
  • demo_scheduler. When a prospect says "this looks great, can I see it?", the bot shows your Calendly demo event and a booking link in the chat. Growth+

Enable them under Automation > Skills in the dashboard.

Compliance for regulated-industry sales

If you sell into healthcare, financial services, or government, RFQ responses contain compliance answers (HIPAA posture, FedRAMP status, data residency commitments). Two practices:

  1. Keep compliance content version-stamped. Add the audit date to every security-related document filename. The bot cites it; the customer trusts it.
  2. Don't let the bot generate new compliance claims. Set the strictness mode to refuse-when-uncertain rather than helpful-mode. The bot says "I'm not certain this is current; let me get the team to verify" rather than improvising a compliance claim from training data.

Common pitfalls

Common mistakes to avoid:

  • Mixing sales and customer-support knowledge in one workspace. Customer-facing chatbot answers internal pricing logic. Keep them separate.
  • Forgetting to audience-tag internal docs. A new hire's bot accidentally surfaces unredacted past RFP responses with named customers in them. Always audience-tag before deploying.
  • Treating bot drafts as final. Reps copy-paste without review. Send a wrong-but-confident answer. Bot drafts are first drafts; humans always review.
  • Not re-indexing after a pricing change. Bot quotes old pricing. Resync the changed pages or re-upload the updated document after every meaningful change. Resync can miss a small edit such as a new price; see why.

FAQ

Can the bot fill out RFP spreadsheets directly?

Not yet. Bot answers go into chat for review, then the rep copies into the spreadsheet. Direct spreadsheet-fill is on our roadmap for early-access customers; reach out if you'd want it.

Does the bot handle multi-language RFQs?

The underlying LLMs handle most major languages. If you sell internationally, the bot can answer in English from your English-only knowledge base, or you can index translated copies of your docs and route queries by language.

How do I prevent the bot from leaking confidential pricing?

Audience-tag internal pricing docs as internal, and keep them in a separate workspace from anything customer-facing. A source set to internal is never used on a public channel, whether or not the person asking is signed in, so identity verification does not unlock it. See restricting the bot to specific sources.

Can the bot learn from RFPs we lose, not just ones we win?

Yes. Index past RFPs regardless of outcome. The retrieval picks the most similar past response by content, not by win/loss flag. If you want to bias toward winning patterns, raise the Priority on the won responses under Knowledge > [source] > Settings.

Does this work for procurement on the buyer side?

Yes. A buyer's procurement team can use the same pattern in reverse: index vendor responses, RFP requirements, internal procurement policies. The bot helps the buyer draft RFPs and analyze responses.

Was this page helpful?