AI & RAG

Draft RFP and Security Questionnaire Answers from Past Looms and Docs

Takes an uploaded RFP or security questionnaire, answers each row by retrieving from your Loom walkthroughs and Confluence docs.

CategoryAI & RAG
EngineSim + Paperclip
Difficultyadvanced
Triggermanual
Steps6
Setup~25 min

How it runs

The automated pipeline, trigger to output.

  • TriggerRFP or questionnaire file uploadedFilesystem
  • ActionParse file into individual questions
  • ActionRetrieve evidence from Loom and Confluence per questionConfluenceConfluence
  • LogicRoute low-confidence questions to needs-human bucket
  • ActionDraft answers with citations and confidence via OpenAIOpenAI
  • OutputDeliver completed draft and flagged gaps to SlackSlack

What it does

Upload a vendor RFP or security questionnaire and this workflow answers it row by row, grounding each response in your indexed Loom walkthroughs and Confluence documentation. It flags any question it cannot confidently answer so the SE knows exactly where human input is still needed.

When to use it

Use it when RFPs and security reviews eat your SE hours and the answers already exist scattered across demo recordings and docs. It produces a defensible first draft instead of a blank spreadsheet.

How it works

  1. 1An uploaded questionnaire file (CSV or spreadsheet) triggers the flow.
  2. 2An action parses the file into individual questions.
  3. 3For each question, the retriever searches Loom transcripts and Confluence pages for supporting evidence.
  4. 4A logic step routes low-evidence questions into a "needs human" bucket.
  5. 5OpenAI drafts each answer strictly from retrieved sources, attaching a confidence score and citation.
  6. 6The completed draft with flagged gaps is delivered to the SE via Slack for review.

Set it up

What you configure once, before turning it on.

  1. 1
    Connect FilesystemRead and write files in the workspace volume.
  2. 2
    Connect LoomVideo transcripts, libraries.
  3. 3
    Connect ConfluenceSpaces, pages, blueprints.
  4. 4
    Connect OpenAIModels, embeddings, files.
  5. 5
    Connect SlackChannels, DMs, threads, mentions.
  6. 6
    Set each agent's modelWe leave models unset so you pick the tier — fast + cheap, or top-quality.
  7. 7
    Tune it to your dataEdit the prompts, filters, and field mappings so it matches how your team works.
  8. 8
    Test, then turn it onRun once against a sample, confirm the output, then enable the trigger.

Run this workflow in your colony.

14-day trial. No DevOps. No Sales call. Provisioned in under a minute.