ML model automates support ticket classification and routing
Client: Mid-sized network appliance provider (California) | Solution: ML-based ticket engine classified and routed support requests with zero manual intervention.
Support teams faced triage bottlenecks
Engineers manually reviewed every ticket to tag issues and assign teams. This slowed response times, caused misrouting, and created backlogs. Historical ticket data sat unused with no automated learning or pattern recognition in place.
Solution
Calsoft deployed a BERT-based classification engine that analyzed ticket content and routed requests automatically to the correct teams.
- Trained model on historical ticket patterns and labels
- Scored predictions by confidence and flagged uncertain cases
- Connected via REST API to existing ticketing workflows
- Enabled retraining loops based on resolution feedback
The system reduced manual effort while maintaining accuracy across high ticket volumes.
Business Value
Faster triage
Automated ticket classification cut assignment delays from hours to seconds
Higher SLA compliance
Accurate routing improved on-time resolution rates across all ticket types
Better team utilization
Matched requests to available teams based on workload and expertise
Fewer escalations
Correct first-touch assignments eliminated multi-level handoffs
To Know More
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