Support Inbox Triage with AI Classification
We introduced AI-based ticket classification and routing so support leads could reduce queue time without adding headcount.
Automatic triage moved urgent tickets to the right queue in seconds instead of manual sorting.
Routing rules and confidence thresholds reduced the number of misrouted tickets that bounced between teams.
Agents spent less time on categorization and more time resolving customer issues.
The model hit target accuracy after adding a weekly review loop with support leads.
Project Details
Problem
The client handled support via shared inboxes and manual tags. During release weeks, ticket volume spiked and urgent issues were buried in low-priority requests.
Approach
We built an AI triage pipeline that classifies intent, urgency, and account tier, then routes tickets to team-specific queues. The trade-off was adding a human-review checkpoint for low-confidence predictions to avoid routing mistakes.
Result
Support operations became predictable during peak weeks, with faster first response and fewer queue bottlenecks.
What Could Be Better
Model quality dropped after a major product launch changed ticket language. We stabilized it with weekly retraining on recent conversations.