AI & RAG
Agent completes an entire security questionnaire end to end with review queue
An agent ingests a full uploaded questionnaire, retrieves grounded answers from the policy KB for every item, fills the response document.
How it runs
The automated pipeline, trigger to output.
- TriggerQuestionnaire uploaded via webhookHTTP webhook
- ActionAgent parses and plans question set
- ActionRetrieve passages from versioned KBConfluence
- ActionDraft answers with citations + confidenceOpenAI
- LogicSplit confident vs uncertain answers
- OutputFill response doc + queue review tasksGoogle Drive
What it does
Given a complete security questionnaire, an agent works through every question, retrieves supporting policy from the knowledge base, drafts each answer with citations, and assembles the finished response document. Items it can't ground with sufficient confidence are split into a human review queue rather than shipped.
When to use it
Use it for large multi-hundred-item questionnaires where answering manually is slow but a blanket auto-fill would be risky. The agent handles the volume; the review queue keeps a human in control of the uncertain answers.
How it works
- 1A questionnaire upload via webhook triggers the run.
- 2The agent parses the document and plans the question set.
- 3For each item it retrieves passages from the versioned Confluence KB.
- 4OpenAI drafts answers with citations and a confidence score.
- 5A logic gate separates high-confidence cited answers from uncertain ones.
- 6Confident answers fill the response doc in Google Drive; uncertain items become tasks in Linear for review.
Set it up
What you configure once, before turning it on.
- 1Connect HTTP webhookTrigger any URL on agent actions.
- 2Connect ConfluenceSpaces, pages, blueprints.
- 3Connect OpenAIModels, embeddings, files.
- 4Connect Google DriveDocs, sheets, slides, files.
- 5Connect LinearIssues, projects, cycles, triage.
- 6Set each agent's modelWe leave models unset so you pick the tier — fast + cheap, or top-quality.
- 7Tune it to your dataEdit the prompts, filters, and field mappings so it matches how your team works.
- 8Test, then turn it onRun once against a sample, confirm the output, then enable the trigger.
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Run this workflow in your colony.
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