CUSTOMER SUPPORT
Draft Confluence KB articles from resolved Front conversations
When a Front conversation is archived as resolved, an AI reads the full thread and drafts a new knowledge-base article.
How it runs
The automated pipeline, trigger to output.
- TriggerFront conversation marked resolvedFront
- ActionFetch full conversation threadFront
- LogicSkip threads too short to document
- ActionDraft article from transcriptOpenAI
- OutputCreate unpublished Confluence draftConfluence
What it does
Turns each resolved support conversation into a candidate knowledge-base article. The workflow reads the customer's problem and the agent's resolution from a Front thread, then writes a clean, reusable how-to and parks it as an unpublished Confluence draft awaiting human approval.
When to use it
Use it when your team solves the same problems repeatedly but never has time to document them. Best for support orgs that live in Front and keep their help center in Confluence, and that want a steady trickle of editor-ready drafts rather than a documentation backlog.
How it works
- 1A Front conversation is moved to the resolved/archived state, firing the trigger.
- 2The flow pulls the entire message history, including customer messages and agent replies.
- 3A filter drops threads too short to document (one-line replies, spam, duplicates).
- 4OpenAI summarizes the issue, the cause, and the fix into a structured article with a title, symptoms, and step-by-step resolution.
- 5The draft is created as an unpublished Confluence page in a "Needs Review" space, tagged with the source conversation ID so editors can trace it back.
Set it up
What you configure once, before turning it on.
- 1Connect FrontShared inbox, conversations.
- 2Connect OpenAIModels, embeddings, files.
- 3Connect ConfluenceSpaces, pages, blueprints.
- 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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Run this workflow in your colony.
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