AI classification and routing for 8,000 daily tickets, with sentiment-based escalation to senior agents.
A developer-tools company receives 8,000 support tickets a day across product areas, languages, and severity levels. A tired human triage team sorted them by hand, and critical outages sometimes waited behind routine questions.
Tickets arrived in three channels with inconsistent labels. Sentiment and severity were judged manually, so frustrated customers could wait as long as happy ones. The triage team had 40% annual turnover from the grind.
We trained a lightweight classifier on two years of historical tickets to predict product area, priority, and sentiment. Every incoming ticket is now classified live, routed to the right queue, and surfaced with a confidence score for review. Negative-sentiment tickets touching billing or outages are escalated to senior agents in under 30 seconds.