AI & RAG
Grounded Runbook Answer Bot in Slack with Source-Section Citations
Answers engineers' runbook questions in Slack by retrieving the most relevant Confluence sections and replying with a grounded answer plus deep links to the exact source headings…
How it runs
The automated pipeline, trigger to output.
- TriggerEngineer asks a question via Slack command or mentionSlack
- ActionEmbed the question and retrieve top runbook sections from Postgres pgvectorPostgres
- LogicCheck retrieval confidence; if no relevant section, return a no-answer message
- ActionGenerate a grounded answer with OpenAI using only retrieved contextOpenAI
- OutputPost answer to the Slack thread with deep links to cited Confluence section anchorsSlack
What it does
Turns a Slack slash command or mention into a grounded Q&A bot over your engineering runbook wiki. It retrieves the most relevant runbook sections from a vector index, asks the model to answer using only that retrieved text, and posts the answer back to the thread with citations that deep-link to the exact Confluence heading anchors.
When to use it
Use it when on-call engineers keep asking the same 'how do I restart X' or 'what's the rollback procedure' questions and you want fast, trustworthy answers that always point to the canonical runbook instead of tribal memory.
How it works
- 1An engineer triggers the bot in Slack with a question.
- 2The question is embedded with OpenAI and matched against runbook section vectors stored in Postgres (pgvector).
- 3The top sections are assembled into a context block, each tagged with its Confluence page ID and heading anchor.
- 4OpenAI generates an answer constrained to the retrieved text; if nothing relevant is found it says so rather than guessing.
- 5The reply is posted to the Slack thread with a 'Sources' list linking to each cited section anchor.
Set it up
What you configure once, before turning it on.
- 1Connect SlackChannels, DMs, threads, mentions.
- 2Connect OpenAIModels, embeddings, files.
- 3Connect PostgresAny Postgres URL — query, write, migrate.
- 4Connect ConfluenceSpaces, pages, blueprints.
- 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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