AI & RAG
Incremental runbook re-index on wiki edit
Watches the runbook wiki for page edits and incrementally re-embeds only the changed pages into the vector store.
How it runs
The automated pipeline, trigger to output.
- TriggerConfluence webhook fires on page create or editConfluence
- ActionFetch current page body and metadata from ConfluenceConfluence
- LogicSkip out-of-scope or archived pages
- ActionChunk and embed the page with OpenAIOpenAI
- OutputReplace page vectors in pgvector, version-stampedPostgres
What it does
Maintains the answer bot's knowledge freshness automatically. Whenever a runbook page is created or edited, this workflow re-chunks and re-embeds just that page, replacing its old vectors so retrieval always reflects the latest content without a costly full rebuild.
When to use it
Use it as the indexing backbone for any grounded answer bot over a frequently edited wiki, when you cannot tolerate the bot serving answers from a stale snapshot and a nightly full re-index is too slow or too expensive.
How it works
- 1A Confluence webhook fires on page create or update, carrying the page ID.
- 2The flow fetches the page's current body and metadata from Confluence.
- 3A logic step checks whether the page is in scope (correct space, not archived) and skips if not.
- 4The page is chunked and embedded via OpenAI.
- 5Old vectors for that page ID are deleted and the new ones upserted in the Postgres pgvector index, version-stamped for the freshness auditor.
Set it up
What you configure once, before turning it on.
- 1Connect ConfluenceSpaces, pages, blueprints.
- 2Connect OpenAIModels, embeddings, files.
- 3Connect PostgresAny Postgres URL — query, write, migrate.
- 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.
Run this workflow in your colony.
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