Case Study

AI Customer Service

An intelligent assistant and routing system that improved response time and deflection rates.

Client

A consumer services company facing large support volumes and slow response SLA.

Challenge

High ticket volumes, repetitive questions and long waiting times impacted customer satisfaction.

Outcome

  • 80% faster average response times
  • High deflection via automated self-service flows
  • Improved CSAT and lower support costs
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AI Customer Service

Approach

Intent classifiation & NLU

Trained models to understand user intents and extract entities from support messages.

Automated flows

Design of conversation flows and escalation rules to route complex queries to agents.

Monitoring

Measure deflection, fallback rates, and continuously refine knowledge base.