Customer Support Agent

Overview

Built a conversational agent that understands context, accesses customer data securely, resolves common issues, and escalates intelligently when needed....

The Problem

A consumer fintech was scaling fast but support costs were scaling faster. Response times were slipping. Customer satisfaction was dropping. Hiring more agents was not sustainable.

The Solution

Built a conversational agent that understands context, accesses customer data securely, resolves common issues, and escalates intelligently when needed.

Architecture

• Intent classification with fallback detection
• Retrieval-augmented generation for knowledge base
• Secure API layer for account operations
• Conversation memory and context management
• Escalation logic with sentiment detection
• Analytics dashboard for continuous improvement

Business Impact

• 70% of tickets resolved without human intervention
• Average response time dropped from 4 hours to 30 seconds
• Support costs reduced by 45%
• CSAT improved from 3.8 to 4.4

Lessons Learned

• Edge cases define user experience - handle them gracefully
• Escalation is a feature not a failure
• Tone matters as much as accuracy
• Start narrow and expand scope incrementally

Next Steps

• Voice channel support
• Proactive outreach
• Multi-language expansion