AI & RAG

Draft RFP answers from your policy + past-answer corpus

When a new RFP document lands in Google Drive, retrieves matching policies and previously approved answers.

CategoryAI & RAG
Enginesim
Difficultyintermediate
Triggerevent
Steps6
Setup~15 min

How it runs

The automated pipeline, trigger to output.

  • TriggerNew RFP file in Drive intake folderGoogle DriveGoogle Drive
  • ActionParse document and split into questions
  • ActionRetrieve matching past answers + policiesOpenAI
  • LogicFlag questions with no confident match as needs-SME
  • ActionDraft grounded answer per question with citationsOpenAI
  • OutputCreate reviewable answer doc in NotionNotionNotion

What it does

Turns a freshly uploaded RFP into a ready-to-edit answer draft. Each question is matched against your curated corpus of approved past answers and policy documents, and an LLM writes a grounded response that cites which source it drew from. Nothing is sent to the customer automatically — a reviewer gets a clean Notion doc to approve or edit.

When to use it

Use this when sales or pre-sales receives RFPs as files (Word, PDF, spreadsheet) and your team currently re-answers the same questions by hand. Best when you maintain a trusted library of prior answers and want consistency without copy-paste.

How it works

  1. 1A new file dropped into the RFP intake folder in Google Drive triggers the run.
  2. 2The file is parsed and split into discrete questions.
  3. 3Each question is embedded and used to retrieve the top matching past answers and policy snippets from your corpus.
  4. 4An LLM drafts an answer per question, grounded only in retrieved sources, flagging any question with no good match as 'needs SME'.
  5. 5A structured Notion review doc is created with question, draft answer, cited sources, and a confidence label for a human to approve.

Set it up

What you configure once, before turning it on.

  1. 1
    Connect Google DriveDocs, sheets, slides, files.
  2. 2
    Connect OpenAIModels, embeddings, files.
  3. 3
    Connect NotionPages, databases, comments.
  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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