AI & RAG

Answer SOP questions raised in Confluence comments with Dropbox grounding

When a field tech asks a question in a Confluence comment, this grounds it against the authoritative Dropbox SOP corpus and posts a cited reply inline.

CategoryAI & RAG
Enginesim
Difficultyintermediate
Triggerevent
Steps5
Setup~15 min

How it runs

The automated pipeline, trigger to output.

  • TriggerNew comment posted on a watched Confluence spaceConfluenceConfluence
  • LogicDetect whether the comment is a real question
  • ActionRetrieve grounding passages from the Dropbox SOP corpusDropboxDropbox
  • ActionDraft a grounded answer with OpenAIOpenAI
  • OutputReply inline on the Confluence comment with citationsConfluenceConfluence

What it does

Teams that live in Confluence often ask procedural questions right in the page comments. This workflow watches for new comments that look like questions, retrieves the relevant procedures from the authoritative Dropbox SOP corpus, and replies in the same comment thread with a grounded answer and links to the source files. It keeps Confluence as the discussion surface while Dropbox stays the single source of truth.

When to use it

Use it when your written procedures live in Dropbox but day-to-day discussion and questions happen on Confluence pages. It bridges the two without forcing techs to leave the page they are reading.

How it works

  1. 1A new comment posted on a watched Confluence space triggers the run.
  2. 2A logic step checks the comment is a genuine question and not chatter.
  3. 3The question is retrieved against the Dropbox SOP index, returning the best passages and file links.
  4. 4OpenAI drafts an answer grounded only in those passages.
  5. 5The answer, with Dropbox citation links, is posted as a reply on the original Confluence comment thread.

Set it up

What you configure once, before turning it on.

  1. 1
    Connect ConfluenceSpaces, pages, blueprints.
  2. 2
    Connect DropboxFiles and folders.
  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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