TICKET MANAGEMENT
Agent-Driven Known-Issue Suggester on Zendesk Ticket Update
When an agent updates a Zendesk ticket, a Paperclip agent investigates prior solved tickets and the Confluence runbook.
How it runs
The automated pipeline, trigger to output.
- TriggerZendesk ticket updatedZendesk
- ActionAgent reads ticket thread and frames the problemOpenAI
- ActionSearch Confluence runbook and solved-ticket archiveConfluence
- LogicEvaluate candidates and gate on confidence
- OutputPost tailored known-issue suggestion as private commentZendesk
What it does
This is an investigative assistant that fires whenever an agent adds a comment or changes a ticket field. A Paperclip agent reads the full thread, searches both the solved-ticket history and the Confluence known-issues runbook, reasons about which known issue best fits, and writes a private suggestion with reproduction steps adapted to the customer's reported environment.
When to use it
Use this when ticket context evolves mid-conversation and a one-shot match at creation time is not enough. The agent re-evaluates on each update, so its suggestion sharpens as the customer supplies more detail.
How it works
- 1A Zendesk ticket update (new comment or field change) triggers the flow.
- 2The Paperclip agent reads the current ticket thread and identifies the candidate problem area.
- 3It searches the Confluence runbook and the solved-ticket archive for matching known issues.
- 4It evaluates candidates and decides whether confidence is high enough to suggest.
- 5If confident, it tailors the reproduction steps to the customer's stated setup.
- 6It posts a private internal comment on the Zendesk ticket with the suggested known issue, repro steps, and source links.
Set it up
What you configure once, before turning it on.
- 1Connect ZendeskTickets, queues, knowledge base.
- 2Connect ConfluenceSpaces, pages, blueprints.
- 3Connect OpenAIModels, embeddings, files.
- 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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