The company handled very high volumes of support requests from consumers, merchants, and delivery workers. Contact-center capacity was under pressure, especially for routine issues that could be resolved through self-service.

An AI voice-support agent uses speech recognition, LLMs, low-latency response generation, knowledge retrieval, workflow automation, and escalation logic. It understands common support requests, retrieves relevant answers, completes routine workflows where possible, and routes complex or sensitive cases to human support.

• 49% lessAgent transfers after self-service automation
• 12% moreFirst-contact resolution
• ≤2.5 secResponse latency
• Routine support capacity increased without proportional contact-center expansion

Enterprise example · The problem & approach apply across business sizes; outcomes vary by process volume, complexity & scope