AI AGENTS
Re-validate cached questionnaire answers when a policy changes
When a security policy page is edited in Confluence, an agent finds every saved questionnaire answer that cited it and re-checks whether the answer is still accurate.
How it runs
The automated pipeline, trigger to output.
- TriggerPolicy page updated in ConfluenceConfluence
- ActionIdentify what changed in the policy
- ActionFind cached answers citing this policyPostgres
- LogicClassify each answer: consistent, outdated, needs-rewrite
- ActionMark outdated answers stale in libraryPostgres
- OutputPost drift summary to SlackSlack
What it does
Keeps your answer library honest. The moment a policy changes, it locates the canned answers that were built on that policy and verifies each one still matches the updated text, so you never send a vendor an answer that contradicts your current controls.
When to use it
Use this if you maintain a reusable answer bank and your policies actually change over time (new MFA rules, updated retention windows, vendor swaps). Prevents stale answers from silently going out in future questionnaires.
How it works
- 1A page update in the Confluence security space triggers the run.
- 2The agent reads the new version and identifies what materially changed.
- 3It queries the answer library in Postgres for every cached answer referencing that policy.
- 4It compares each answer against the revised policy and labels it consistent, outdated, or needs-rewrite.
- 5Outdated answers are marked stale in the library and a summary of affected answers is posted to Slack for the compliance owner.
Set it up
What you configure once, before turning it on.
- 1Connect ConfluenceSpaces, pages, blueprints.
- 2Connect PostgresAny Postgres URL — query, write, migrate.
- 3Connect SlackChannels, DMs, threads, mentions.
- 4Set each agent's modelWe leave models unset so you pick the tier — fast + cheap, or top-quality.
- 5Tune it to your dataEdit the prompts, filters, and field mappings so it matches how your team works.
- 6Test, then turn it onRun once against a sample, confirm the output, then enable the trigger.
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Run it inside a business
This workflow drops into a full company template. Import the org, and this is one of the playbooks its agents run.

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