AI & RAG

Runbook Answer Bot with Required Citations in Slack

Answers on-call and ops questions in Slack by grounding every reply in your Confluence + Drive runbook corpus, and refuses to answer when no supporting source exists.

CategoryAI & RAG
Enginesim
Difficultyintermediate
Triggerevent
Steps5
Setup~15 min

How it runs

The automated pipeline, trigger to output.

  • TriggerSlack message or @mention in #ops-helpSlack
  • ActionEmbed question and retrieve top runbook passagesPostgreSQLPostgres
  • LogicGate on retrieval confidence; reply 'not documented' if low
  • ActionCompose grounded answer with source IDsOpenAI
  • OutputPost answer with inline citations to Slack threadSlack

What it does

Turns a Slack channel into a runbook help desk. When someone asks a procedural question, the agent retrieves the most relevant passages from your indexed Confluence pages and Google Drive docs, drafts an answer, and posts it back with inline citations linking to each source. If retrieval surfaces nothing above the confidence threshold, it says so plainly instead of guessing.

When to use it

Use it when on-call engineers, support agents, or new hires keep asking 'how do I...' questions that are already documented but hard to find. It cuts repeated interruptions to senior staff and keeps answers traceable to a canonical doc.

How it works

  1. 1A Slack message in the watch channel (or an app mention) triggers the flow.
  2. 2The question is embedded and matched against the runbook vector index in Postgres.
  3. 3A logic gate checks retrieval score: below threshold, it short-circuits to a 'not documented' reply.
  4. 4OpenAI composes an answer constrained to the retrieved passages, emitting source IDs.
  5. 5The bot posts the answer to the Slack thread with clickable citations to each Confluence or Drive source.

Set it up

What you configure once, before turning it on.

  1. 1
    Connect SlackChannels, DMs, threads, mentions.
  2. 2
    Connect PostgresAny Postgres URL — query, write, migrate.
  3. 3
    Connect OpenAIModels, embeddings, files.
  4. 4
    Connect ConfluenceSpaces, pages, blueprints.
  5. 5
    Connect Google DriveDocs, sheets, slides, files.
  6. 6
    Set each agent's modelWe leave models unset so you pick the tier — fast + cheap, or top-quality.
  7. 7
    Tune it to your dataEdit the prompts, filters, and field mappings so it matches how your team works.
  8. 8
    Test, then turn it onRun once against a sample, confirm the output, then enable the trigger.

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