TICKET MANAGEMENT
SLA Pause Auditor: Agent Investigates Whether a 'Met' SLA Was Actually Breached
On demand for a single ticket, an agent reconstructs the full pause-and-reply timeline, judges whether each 'waiting on customer' pause was legitimate.
How it runs
The automated pipeline, trigger to output.
- TriggerChat request supplies a ticket ID to investigate
- ActionFetch full audit history and comments from ZendeskZendesk
- LogicMap each pause interval to who was actually responsible
- ActionJudge each pause and recompute true SLA outcomeOpenAI
- OutputReturn cited written verdict to the requester
What it does
This is an investigator you can point at one disputed ticket. Given a ticket ID, the agent pulls the complete event history from Zendesk, lines up every clock pause against the actual conversation, and reasons about each pause: was the customer genuinely the blocker, or did the agent pause the timer while the ball was in their own court? It produces a written verdict — SLA legitimately met, or met only because of an improper pause — with the specific intervals cited.
When to use it
Use it when an agent contests an SLA finding, a customer escalates claiming slow service despite a 'met' SLA, or QA needs a defensible narrative for one ticket rather than a batch metric.
How it works
- 1A chat request supplies the ticket ID to investigate.
- 2The agent fetches the ticket's full audit history and comments from Zendesk.
- 3It reconstructs each pause interval and maps it to who was actually responsible at that moment.
- 4It judges each pause as legitimate or improper and recomputes the true SLA outcome.
- 5It returns a cited written verdict to the requester.
Set it up
What you configure once, before turning it on.
- 1Connect ZendeskTickets, queues, knowledge base.
- 2Connect OpenAIModels, embeddings, files.
- 3Set each agent's modelWe leave models unset so you pick the tier — fast + cheap, or top-quality.
- 4Tune it to your dataEdit the prompts, filters, and field mappings so it matches how your team works.
- 5Test, then turn it onRun once against a sample, confirm the output, then enable the trigger.
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Run it inside a business
This workflow drops into a full company template. Import the org, and this is one of the playbooks its agents run.
Run this workflow in your colony.
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