AI & RAG

Draft RFP security answers from versioned policy KB with citation gating

Watches a Google Drive folder for new security questionnaires, drafts answers from your versioned policy knowledge base, and only keeps answers backed by a cited source.

CategoryAI & RAG
Enginesim
Difficultyintermediate
Triggerevent
Steps6
Setup~15 min

How it runs

The automated pipeline, trigger to output.

  • TriggerNew questionnaire file in Drive intake folderGoogle DriveGoogle Drive
  • ActionParse file into individual questions
  • ActionRetrieve policy passages from versioned KBConfluenceConfluence
  • ActionDraft grounded answer with citationsOpenAI
  • LogicGate: drop answers lacking valid citations
  • OutputWrite draft + review list back to DriveGoogle DriveGoogle Drive

What it does

When a vendor security questionnaire lands in your intake folder, this workflow reads each question, retrieves the most relevant approved policy passages from your knowledge base, and drafts a grounded answer. Any answer that cannot be tied to a real source citation is withheld and routed to a human instead of being guessed.

When to use it

Use it when your team fields recurring SIG, CAIQ, or custom security questionnaires and you want fast first drafts without inventing claims. The citation gate keeps unsupported language out of buyer-facing responses.

How it works

  1. 1A new questionnaire file in the Google Drive intake folder triggers the run.
  2. 2The file is parsed into individual question rows.
  3. 3For each question, relevant passages are retrieved from the versioned policy KB in Confluence.
  4. 4OpenAI drafts an answer constrained to the retrieved passages and emits a citation list.
  5. 5A logic gate drops or flags any answer with zero valid citations.
  6. 6The completed draft, with citations and a review-needed list, is written back to Google Drive.

Set it up

What you configure once, before turning it on.

  1. 1
    Connect Google DriveDocs, sheets, slides, files.
  2. 2
    Connect ConfluenceSpaces, pages, blueprints.
  3. 3
    Connect OpenAIModels, embeddings, files.
  4. 4
    Set each agent's modelWe leave models unset so you pick the tier — fast + cheap, or top-quality.
  5. 5
    Tune it to your dataEdit the prompts, filters, and field mappings so it matches how your team works.
  6. 6
    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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