Teams were blind to confusion. Now, AI tracks 48 emotions per word, flagging anxiety to guide targeted coaching.
A conversational intelligence platform analyzes human interactions for organizations ranging from customer contact centers to correctional departments.
Traditional sentiment tools relied on binary classifications and general tonal scoring, often missing subtle emotional shifts like confusion or...
“We were blind to what our customers were feeling until we had emotion as a signal. Now we coach smarter and intervene faster.”
Conversational intelligence and automation platform for customer experience and QA.
AI platform for building expressive, emotionally intelligent voice applications.
Related implementations across industries and use cases
Manual tests missed emotional cues. Simulations now stress-test agent empathy, catching failures before they reach real users.
95% of recorded calls went unreviewed. AI now separates speakers live, feeding instant coaching cues to agents as they speak.
Staffing costs held back 24/7 scale. AI agents now automate millions of calls with voices so human that clients ask for them by name.
Surveys missed 95% of data and took weeks to analyze. AI now scans 100% of interactions, identifying churn risks in seconds.
Generic tools missed product names, skewing data. Tailored models now master niche jargon using just 20 hours of sample audio.
Data policies blocked collaboration. Federated AI detects signals 10x faster, syncing global observatories without exposing raw data.
Drowning in 80,000 monthly alerts, analysts struggled to secure data. AI now prioritizes threats, cutting response time by 99%.
Experts spent 15 minutes pulling data from scattered systems. Natural language prompts now generate detailed reports instantly.
Lab supply orders were handwritten in notebooks. Digital ordering now takes seconds, saving 30,000 hours for research annually.