AI & RAG
Index incident postmortems into a searchable runbook knowledge base
Watches a Notion postmortem database for newly completed reports, chunks and embeds them.
How it runs
The automated pipeline, trigger to output.
- TriggerEvery 30 min, check Notion for newly completed postmortemsNotion
- ActionFetch full page content and extract timeline, root cause, remediationNotion
- LogicSkip pages whose content hash already exists in the index
- ActionChunk text and generate embeddingsOpenAI
- OutputUpsert vectors and metadata into Postgres pgvector tablePostgres
What it does
Keeps the answerbot's knowledge base current by ingesting every finished incident postmortem. When a postmortem in Notion is marked complete, this pipeline extracts the text, splits it into retrieval-sized chunks, generates embeddings, and stores them in a Postgres vector table alongside metadata like severity, affected service, and incident date.
When to use it
Run this as the backbone of any oncall answerbot. Set it up once and every new postmortem your team writes automatically becomes retrievable knowledge, without a manual re-index step.
How it works
- 1A schedule fires every 30 minutes and queries the Notion postmortem database for pages whose status changed to Complete since the last run.
- 2For each page, it pulls the full block content and normalizes headings (timeline, root cause, remediation) into clean text.
- 3The text is chunked with overlap and sent to OpenAI for embeddings.
- 4A logic step skips pages whose content hash already exists, preventing duplicate vectors.
- 5Embeddings plus metadata are upserted into the Postgres pgvector table that the answerbot queries.
Set it up
What you configure once, before turning it on.
- 1Connect NotionPages, databases, comments.
- 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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