Available
SLM-Works Support Classifier
Instant ticket routing and intent detection
Classifies support traffic in real time to reduce triage bottlenecks and improve SLA routing discipline.
How it works
Step 1
Read inbound ticket text and metadata.
Step 2
Predict category, urgency, and sentiment in one pass.
Step 3
Map outcome to queue ownership and SLA policy.
Step 4
Write structured routing data back to your support platform.
Example
Example input
Ticket: 'API calls time out after 2 PM. Customers blocked in checkout flow.'
Example output
{ category: 'incident', urgency: 'high', sentiment: 'negative', route_to: 'SRE-oncall' }
Key features
- Multi-label classification for category + urgency + sentiment
- Sub-10ms inference profile for queue-time decisions
- Native adapters for ServiceNow/Jira/Zendesk pipelines
- Configurable taxonomy per team
Rollout guidance
- Calibrate urgency classes with incident postmortems.
- Version taxonomy updates to avoid drift in reporting.
Ideal for
FAQ
Can we override model decisions?
Yes. Manual override and feedback loops should be part of every production rollout.
Want this model in your stack?
We can scope a deployment blueprint, evaluation set, and integration plan for your data and infrastructure constraints.