AI & RAG

Confluence Team-Space Answer Bot in Slack

Answers Slack questions using only your team's Confluence space, citing the exact pages it pulled from. Replies in-thread or says it doesn't know rather than guessing.

CategoryAI & RAG
Enginesim
Difficultyintermediate
Triggerevent
Steps5
Setup~15 min

How it runs

The automated pipeline, trigger to output.

  • TriggerSlack mention or channel message receivedSlack
  • ActionSearch Confluence within the team space keyConfluenceConfluence
  • LogicFilter by relevance; bail if no page qualifies
  • ActionDraft grounded answer with citations via OpenAIOpenAI
  • OutputReply in the Slack thread with source linksSlack

What it does

Gives your team a Slack-native answer bot grounded strictly in one Confluence space. When someone @-mentions the bot or posts in a designated channel, it retrieves the most relevant pages from that single space, drafts an answer with OpenAI, and replies in-thread with linked citations. If nothing relevant is found, it says so instead of hallucinating.

When to use it

Use it when a team wants self-serve answers from their own documented knowledge without people digging through Confluence. Ideal for onboarding questions, runbooks, and policy lookups where answers must be traceable to source pages.

How it works

  1. 1A Slack message mention triggers the flow.
  2. 2The bot searches Confluence, restricted to the configured team space key, for pages matching the question.
  3. 3A relevance check filters out low-scoring hits; if none pass, the bot posts a polite "not documented here" reply.
  4. 4OpenAI composes an answer using only the retrieved page text, with inline source references.
  5. 5The reply, including Confluence page links, is posted back to the originating Slack thread.

Set it up

What you configure once, before turning it on.

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

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