AI & RAG
Nightly RFC + Code Index Builder for Confluence and GitHub
Runs nightly to pull updated Confluence RFC pages and GitHub source files, chunk and embed them.
How it runs
The automated pipeline, trigger to output.
- TriggerNightly schedule fires
- ActionFetch changed Confluence pages since watermarkConfluence
- ActionFetch files from new GitHub commitsGitHub
- ActionChunk + embed documents with traceback IDsOpenAI
- OutputUpsert vectors and prune deleted sources in SupabaseSupabase
What it does
Keeps the retrieval index behind your RFC answer-bot current. Each night it fetches Confluence pages changed since the last run and GitHub files touched by recent commits, splits them into citation-friendly chunks, embeds them, and upserts the vectors into Supabase. Deleted pages and files are pruned so stale answers don't surface.
When to use it
Whenever you run a RAG answer-bot over Confluence and GitHub and need the index to track edits without manual reindexing. Run this before deploying any of the query-side templates.
How it works
- 1A nightly schedule fires the index build.
- 2The flow lists Confluence pages updated since the last watermark and GitHub files from new commits.
- 3Each document is chunked with stable IDs that carry the source URL and line range for later traceback.
- 4OpenAI generates embeddings for every new or changed chunk.
- 5Chunks are upserted into the Supabase vector table; rows for removed sources are deleted.
- 6The new watermark timestamp is written back for the next run.
Set it up
What you configure once, before turning it on.
- 1Connect ConfluenceSpaces, pages, blueprints.
- 2Connect GitHubRepos, issues, pull requests, actions.
- 3Connect OpenAIModels, embeddings, files.
- 4Connect SupabaseTables, auth, storage, edge functions.
- 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 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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