AI & RAG
Answer citation freshness audit
Reviews recent policy-bot answers, re-checks each cited source against the live Confluence and Drive documents.
How it runs
The automated pipeline, trigger to output.
- TriggerDaily schedule fires
- ActionRead recent answers + citations from SupabaseSupabase
- ActionRe-fetch live state of cited Confluence/Drive docsConfluence
- LogicFlag answers with changed or deleted sources
- OutputMark needs-review in Supabase + Slack digestSlack
What it does
Guards against stale answers. It reads the log of answers your policy bot has given, re-fetches every cited source, and detects when the underlying document has been edited or removed since the answer went out. Affected answers are flagged for follow-up.
When to use it
Use it when policy changes frequently and you have already given automated answers that may now be wrong. It is a trust-and-safety layer for any deployed RAG Q&A system, surfacing answers that need a correction or re-send.
How it works
- 1A scheduled trigger starts the audit (e.g. daily).
- 2The workflow reads recent answers and their cited source IDs from the Supabase answer log.
- 3It re-fetches each citation's current state from Confluence and Drive.
- 4A diff check flags answers whose sources changed materially or no longer exist.
- 5Flagged answers are written back to Supabase as needs-review and a digest is posted to Slack for the owning team.
Set it up
What you configure once, before turning it on.
- 1Connect SupabaseTables, auth, storage, edge functions.
- 2Connect ConfluenceSpaces, pages, blueprints.
- 3Connect Google DriveDocs, sheets, slides, files.
- 4Connect SlackChannels, DMs, threads, mentions.
- 5Set each agent's modelWe leave models unset so you pick the tier — fast + cheap, or top-quality.
- 6Tune it to your dataEdit the prompts, filters, and field mappings so it matches how your team works.
- 7Test, 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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