CUSTOMER SUPPORT
Flag stale help docs that keep generating tickets
On a schedule, cross-references tickets against the help articles that should have deflected them.
How it runs
The automated pipeline, trigger to output.
- TriggerScheduled run fires
- ActionFetch solved tickets from ZendeskZendesk
- ActionMap tickets to owning Confluence articles (OpenAI)OpenAI
- LogicKeep articles over the ticket threshold
- ActionDraft update recommendation per article (OpenAI)OpenAI
- OutputOpen Linear issue for the docs teamLinear
What it does
This workflow connects support volume back to the docs that own each topic. On a schedule it pulls recently solved Zendesk tickets, matches each to the Confluence article that covers it, and counts how many tickets each article failed to deflect. For articles above a threshold, OpenAI drafts a specific edit recommendation and the workflow opens a Linear issue assigned to the docs team.
When to use it
Use this when you suspect certain help articles exist but are confusing, outdated, or hard to find, and you want a steady backlog of doc fixes driven by real ticket pressure rather than guesswork.
How it works
- 1A schedule triggers the run.
- 2The flow fetches recently solved tickets from Zendesk and the article set from Confluence.
- 3OpenAI maps each ticket to its owning article and tallies failed deflections per article.
- 4A logic step keeps only articles over the ticket threshold.
- 5OpenAI drafts a concrete update recommendation for each.
- 6The workflow opens a Linear issue per flagged article for the docs team.
Set it up
What you configure once, before turning it on.
- 1Connect ZendeskTickets, queues, knowledge base.
- 2Connect ConfluenceSpaces, pages, blueprints.
- 3Connect OpenAIModels, embeddings, files.
- 4Connect LinearIssues, projects, cycles, triage.
- 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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Run this workflow in your colony.
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