> ## Documentation Index
> Fetch the complete documentation index at: https://relevanceai-docs-tsp-1307.mintlify.site/llms.txt
> Use this file to discover all available pages before exploring further.

# RFP and security questionnaire responses

> Pull from your archive of prior answers to draft consistent, accurate responses to questionnaires.

Every SE team has the same archive — last year's RFPs, last quarter's security questionnaires, the architecture answers written six different ways across six different deals. An RFP Agent reads each new question and pulls the best prior answer, adapts it to the deal context, and flags anything that needs human judgment.

## When this pays off

<CardGroup cols={2}>
  <Card title="Same answers, six versions" icon="copy">
    The data-residency answer exists in 12 prior RFPs, all slightly different. New responses pick whatever's easiest to find.
  </Card>

  <Card title="Questionnaires take days" icon="hourglass">
    An 80-question security questionnaire eats two SE days. The deal slows because the document is the bottleneck.
  </Card>

  <Card title="Inconsistent answers across deals" icon="scale-unbalanced">
    Security or compliance answers vary by who wrote them, not by what's true. Risky for trust and contracts.
  </Card>

  <Card title="Archive is unsearchable" icon="folder-magnifying-glass">
    "Have we answered this before?" requires a 20-minute hunt across Drive, Notion, and Slack.
  </Card>
</CardGroup>

## The shape of this use case

An RFP Agent takes a question + opportunity context and returns a drafted answer with sources.

<CardGroup cols={2}>
  <Card title="Inputs" icon="arrow-right-to-bracket">
    Question text, opportunity context (segment, geography, deal size), prior-answer archive.
  </Card>

  <Card title="Sources" icon="globe">
    Past RFP and security questionnaire responses, policy docs, architecture artifacts, product changelog.
  </Card>

  <Card title="Output" icon="file-lines">
    A drafted answer with citations to source documents and a confidence indicator — high-confidence answers ready to send, low-confidence flagged for SE review.
  </Card>

  <Card title="Delivery" icon="paper-plane">
    Drafted into the response doc (Google Doc, [Notion](/integrations/popular-integrations/notion), Loopio export), posted in [Slack](/integrations/popular-integrations/slack) for SE review on flagged answers.
  </Card>
</CardGroup>

## Where to start

Two ways in, depending on whether you want something running today or built to your exact spec.

<CardGroup cols={2}>
  <Card title="Clone a pre-built Agent" icon="copy">
    Open the **[AI RFP Response Generator](https://marketplace.relevanceai.com/listing/d1092947-1746-4df1-9596-255d13796a2c)**. More in the [Marketplace](/get-started/marketplace/introduction).
  </Card>

  <Card title="Build your own" icon="hammer">
    Start from scratch in the [builder](/build/introduction), or by describing it in Claude Code or Cursor with [Programmatic GTM](/get-started/core-concepts/programmatic-gtm).
  </Card>
</CardGroup>

Either way, these are prompts your SEs can use on day one:

* *"What's our standard answer to 'describe your data residency options'? Cite past responses."*
* *"This question is asking about SOC 2 controls around access. Pull the right answer and adapt it for an enterprise EU customer."*
* *"Walk me through these 30 questions from Acme's questionnaire — flag the ones that need real SE attention."*

## Where to take it

Once it's running, deepen it in three moves:

<CardGroup cols={3}>
  <Card title="Give it a playbook" icon="book">
    Shape it with a [prompt](/build/agents/build-your-agent/prompt), your prior-response archive in [Knowledge](/build/knowledge/create-knowledge), and [Bulk Schedule](/build/agents/give-your-agent-tasks/bulk-schedule).
  </Card>

  <Card title="Automate it on signals" icon="bolt">
    Wrap it in a [workflow](/build/workforces/create-a-workforce) that fires on a [trigger](/build/agents/build-your-agent/triggers).
  </Card>

  <Card title="Let it improve" icon="arrows-rotate">
    Feed back which answers customers accepted into the Agent's [evals](/build/agents/build-your-agent/evals) so it promotes the strong ones.
  </Card>
</CardGroup>

## Common pitfalls

<AccordionGroup>
  <Accordion title="Hallucinated security claims" icon="user-shield">
    The Agent confidently states a control you don't have. Force citations to actual policy / past-answer documents and fail visibly when the question isn't covered.
  </Accordion>

  <Accordion title="Stale answers" icon="calendar-xmark">
    Last year's accurate answer is this year's misrepresentation. Tag prior responses with dates and have the Agent prefer recent over old when in conflict.
  </Accordion>

  <Accordion title="No human review on legal/security" icon="scale-unbalanced">
    Some questions need legal sign-off. Always route security and contractual answers through human review until you've watched it for several deals.
  </Accordion>

  <Accordion title="Auto-applying without deal context" icon="sitemap">
    A "yes" to a feature in mid-market might be a "yes, but" in enterprise. Have the Agent read the opportunity record and adapt — not just look up the question.
  </Accordion>
</AccordionGroup>