AI & RAG
Keep the Coda Knowledge Index Fresh on Every Row Edit
When a row in the Coda knowledge hub is added or edited, this workflow regenerates its embedding with OpenAI and upserts it into a Postgres pgvector store.
How it runs
The automated pipeline, trigger to output.
- TriggerCoda row added or edited webhookCoda
- ActionRead full current row content and source linkCoda
- LogicBranch: skip draft or archived rows
- ActionGenerate embedding for row textOpenAI
- OutputUpsert vector, row ID, and source URL into Postgres pgvectorPostgres
What it does
Maintains the vector index that powers your grounded answer bot. Whenever a knowledge row changes in Coda, it re-embeds just that row and upserts the vector into Postgres, so retrieval always reflects the current source of truth and citations never point to stale text.
When to use it
Use it as the indexing backbone for any Coda-grounded RAG system. Especially valuable when your knowledge hub changes often and you can't afford a full nightly re-embed of every row.
How it works
- 1A Coda row-changed webhook triggers the workflow with the affected row ID.
- 2The workflow reads the full current row content from Coda, including the canonical source link.
- 3A logic step skips rows marked draft or archived so only published knowledge is indexed.
- 4OpenAI generates an embedding for the row's text.
- 5The embedding, row ID, source URL, and content hash are upserted into the Postgres pgvector table, replacing any prior vector for that row.
Set it up
What you configure once, before turning it on.
- 1Connect CodaDocs, packs, automations.
- 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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