AI voice intelligence platform
Turning customer conversations into continuous business intelligence -analysing recorded calls and proactively engaging customers through AI voice interactions.
AI voice intelligence platform
Turning customer conversations into continuous business intelligence -analysing recorded calls and proactively engaging customers through AI voice interactions.
Client
Insurance Domain
Year
2026
Services
Mobile Engineering & UX Research
Category
AI
Overview
Businesses hold thousands of customer conversations, but most of that information stays trapped in audio recordings, manual reviews, and fragmented feedback. Yexoria helped conceptualise and build an AI-powered voice intelligence ecosystem with two connected capabilities: analysing recorded call-centre conversations for sentiment, emotion, and quality, and an AI voice agent that proactively calls customers to collect feedback. Together they form one continuous loop - analyse, understand, engage, learn, improve.
Tech Stack
Key Features
Challenges
- ✦ Valuable conversations were trapped in audio - too much volume to review manually.
- ✦ Customer emotion is difficult to measure with traditional call metrics.
- ✦ Feedback collection was reactive, relying on surveys and complaints rather than proactive outreach.
Outcomes
- ✦ Reduced dependence on manually reviewing large volumes of calls.
- ✦ Surfaced sentiment and emotional signals previously hidden in conversations.
- ✦ Established a proactive, AI-driven feedback loop alongside historical call analysis.
What we delivered
- ✦ Conversation intelligence pipeline analysing recorded calls for sentiment, emotion, and conversation quality
- ✦ AI voice agent built on LiveKit for real-time, proactive customer calls
- ✦ Sarvam AI-powered speech-to-text and text-to-speech tuned for Indian customer interactions
- ✦ Conceptual dashboard experience translating AI output into business-friendly insights
Conclusion
Customer conversations are not just support interactions - they are a source of business intelligence. This engagement combined historical conversation analysis with proactive AI voice engagement into a single, continuous intelligence layer, giving businesses a scalable way to listen, understand, engage, and improve.