Auto Ticket Triage
Triage is where queues lose their FRT. Every minute a ticket spends waiting for L1 to classify it is a minute the SLA clock burns. This playbook reads each incoming ticket, applies your contact-reason taxonomy, sets priority from sentiment and entitlement tier, and routes — in seconds, not the average two-to-five minutes a human triager takes.
The problem
Triage today is usually one of two patterns. Keyword rules in the helpdesk that catch the obvious cases and miss intent on the rest. Or human L1 triage that adds queue time, burns through new agents, and breaks the moment volume spikes on a release day or an outage.
How DataChi runs it
DataCHI reads the full ticket including history and CRM context, applies your taxonomy with confidence scoring, and sets priority from sentiment, entitlement tier, and SLA at risk. Routing follows. On high-confidence tickets, it can stage a first reply for the agent to review and send, with macros and KB links resolved.
What's included
- Multilingual intent and topic classification against your taxonomy
- Priority scoring from sentiment, entitlement, and SLA exposure
- Per-team and per-skill routing rules with overflow handling
- Drafted first reply for agent review on high-confidence cases
- Confidence-based human-in-the-loop fallback to L1
- Reporting on triage accuracy, FRT impact, and mis-route rate
Who it's for
Support leaders running medium to high ticket volume on Zendesk, Intercom, Front, or Help Scout.
Outcomes
- Triage time per ticket in single-digit seconds
- FRT and AHT down across the queue, not just on Tier 1
- Reopen rate and L1→L2 ping-pong measurably reduced
- SLA exposure surfaced before the breach, not after
Related Support playbooks
Ready to run Auto Ticket Triage with DataChi?
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