Automatically analyze NICE contact center data: call transcripts, chat logs, and post-interaction surveys without keyword tagging or sampling. Detect root causes, emotional drivers, and operational friction from every conversation.
NICE is a leading cloud-native contact center platform that helps businesses manage omnichannel support, workforce optimization, and performance analytics. However, structured performance metrics alone don’t reveal why customers are frustrated, what is driving escalations, or where agents are compensating for upstream issues.
This integration unlocks AI-powered behavioral intelligence across NICE’s rich interaction data, turning voice and chat logs into decision-grade insights.
Analyze 100% of call and chat interaction transcripts without manual sorting or keyword tagging in seconds.
Identify where agents are repeatedly covering for broken processes, unclear policies, or delays.
Track evolving sentiment trends in real time across regions and segments.
Run natural language queries like “Why are refund-related tickets rising?” and get structured answers.
Transform qualitative inputs into measurable drivers with traceability.
Merge NICE call/chat data with reviews, surveys, and CRM insights for full-scope behavior trends.
No more manual keyword tagging or small QA batches, analyze 100% of customer interactions at scale.
Surface hidden reasons behind low FCR and repeated contacts (e.g., confusing refund flow, unclear SLAs).
Uncover topics that create the most confusion or support load, directly from call logs.
Track which issues are emerging and how emotionally charged they are across different channels.