Speaker diarization separates agent and customer speech in every call — enabling per-speaker sentiment analysis, agent-specific scoring, and accurate quality evaluation.
Agent vs Customer
Separation
Per-Speaker
Analytics
Automatic
Detection
How audio intelligence capabilities transform your call analytics
AI identifies and labels each speaker in the conversation. No manual tagging needed — agent and customer are separated automatically.
Get individual sentiment scores, talk time, and behavior metrics for each speaker independently.
Score agents based only on what they said — not contaminated by customer speech or background noise.
Upload a multi-speaker call recording. Supports all major audio formats.
Diarization AI identifies each speaker and labels their segments throughout the conversation.
Review individual metrics for each speaker — sentiment, talk time, interruptions, and more.
Automatically identify which speaker is the agent and which is the customer based on conversation patterns.
Separate sentiment analysis for each speaker. Know how the customer felt vs how the agent responded.
Measure talk-to-listen ratio per speaker. Identify agents who dominate conversations vs those who listen.
Analyze conversation flow — interruptions, long pauses, and speaking overlaps.
Handle calls with more than two speakers — conference calls, transfers, and multi-party conversations.
Score agent performance based only on their speech segments, ensuring accurate quality evaluation.
Start analyzing 100% of your calls with AI. No manual QA sampling, no inconsistent scoring, no missed insights.