AI AGENTS

RFP Clarification Question Generator

When an RFP requirements doc is finalized, the agent finds ambiguous or contradictory requirements and drafts a clean list of clarification questions to email the issuing agency.

CategoryAI Agents
Enginepaperclip
Difficultyintermediate
Triggerevent
Steps6
Setup~15 min

How it runs

The automated pipeline, trigger to output.

  • TriggerNotion page marked intake-completeNotionNotion
  • ActionRead requirements textNotionNotion
  • ActionLook up unfamiliar standardsExa
  • ActionGenerate clarification questionsOpenAI
  • LogicAny questions generated?
  • OutputEmail draft question list to proposal leadGmailGmail

What it does

Reads a finalized RFP requirements document and identifies requirements that are vague, internally contradictory, or missing key detail needed to respond. It drafts a numbered list of clarification questions and sends it as a ready-to-review email to the proposal team.

When to use it

Use it right after intake, before drafting begins, when most RFPs allow a vendor Q&A window. Catching ambiguities early prevents wasted drafting and weak assumptions.

How it works

  1. 1A Notion page is marked intake-complete, firing the trigger.
  2. 2The agent reads the full requirements text from the page.
  3. 3Exa checks unfamiliar standards or acronyms so questions are informed, not naive.
  4. 4OpenAI flags ambiguous, conflicting, or underspecified requirements and writes a clarification question for each.
  5. 5A decision step checks whether any questions were generated at all.
  6. 6If questions exist, a formatted draft email is sent to the proposal lead via Gmail for review before submission to the agency.

Set it up

What you configure once, before turning it on.

  1. 1
    Connect NotionPages, databases, comments.
  2. 2
    Connect ExaNeural search across the web.
  3. 3
    Connect OpenAIModels, embeddings, files.
  4. 4
    Connect GmailRead, draft, send, label.
  5. 5
    Set each agent's modelWe leave models unset so you pick the tier — fast + cheap, or top-quality.
  6. 6
    Tune it to your dataEdit the prompts, filters, and field mappings so it matches how your team works.
  7. 7
    Test, then turn it onRun once against a sample, confirm the output, then enable the trigger.

Run this workflow in your colony.

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