Call Center Agent Coaching AI

Overview

A 60-seat call center had a massive performance gap — their best agents had 85% first-call resolution and high CSAT scores, while their worst barely hit 50%. With only 2 QA supervisors reviewing a random 3% of calls, most coaching opportunities were missed. We built an AI coaching system that listens to every call in real-time, provides agents with live suggestions, scores 100% of calls automatically, and generates personalized improvement plans for each agent.

The Challenge

Real-time coaching requires understanding the conversation fast enough to provide useful prompts before the moment passes. The system needed to detect customer intent, identify when an agent is struggling, suggest specific responses, and do it all with low enough latency to be useful in conversation. It also needed to distinguish between situations where the agent needs a script suggestion vs. a knowledge base answer vs. an escalation recommendation.

Our Approach

We built a real-time analysis pipeline that transcribes, analyzes sentiment, and classifies conversation state with sub-second latency. The coaching engine matches the current conversation against a library of best-practice responses learned from top-performing agents' calls. Live prompts appear on the agent's screen — knowledge base answers, suggested responses, compliance reminders, and upsell opportunities. Post-call, every interaction is scored on 15 quality dimensions. Agents get a weekly coaching dashboard showing their strengths, gaps, and specific calls to review.

Key Features

• Real-time call transcription and analysis
• Live coaching prompts on agent screen
• Automatic quality scoring on every call (100% coverage)
• Agent performance dashboard with trend tracking
• Personalized skill gap identification
• Best-practice library from top performers
• Manager coaching priority queue

Results

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