Ticket Classifier
Route and prioritize tickets instantly
Automatically classify inbound support tickets by category, priority, and sentiment, then route them to the right team queue. Eliminates manual triage, ensures SLAs are met, and gives support managers real-time visibility into ticket distribution.
GPT-6 Luna
for 300K tokens a month · 85% input / 15% output
Why this model
For this workload — 300K tokens a month, 85% of them input — it comes to about $0.05 a month, the lowest of the models suggested here.
Alternative models
Implementation tips
- 1
Use structured JSON output mode and define your taxonomy up front — the model is far more consistent when it picks from a fixed enum of 10–15 categories than when it invents its own.
- 2
Run batch processing overnight for non-urgent historical ticket classification, saving 50% on API costs compared to synchronous classification.
- 3
Include a 'reasoning' field in your JSON schema asking the model to explain its classification — this gives your team an audit trail and helps you catch systematic misclassifications.