Your company’s goldmine?
All those meetings and call recordings. It’s the fuel that AI needs.
But here’s the big letdown: those call transcripts only pick up the words. Not what they mean.
And the difference?
Well…. That can make all the difference.
But some new technology might change what’s possible.
Join us as we talk about it.
AI Can Finally Hear What You Actually Mean. What this unlocks — An Everyday AI chat with Jordan Wilson and Modulate’s Mike Pappas.
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Topics Covered in This Episode:
- Modulate Velma Voice Native AI Model Overview
- Tone, Emotion, and Intent in Voice AI
- Differentiating Text vs. True Voice Understanding
- Real-World Voice AI Use Cases in Fraud Detection
- Synthetic Voice and Deepfake Detection Techniques
- Ensemble Listening Model (ELM) Technology Explained
- Voice AI for Customer Service and Support
- Trust, Compliance, and Observability in Voice AI Agents
- Cost and Scalability Challenges for Voice AI
- Future Impact of Voice AI on Customer Relationships
Timestamps:
00:00 "Modulate: AI That Understands Tone"
06:15 "AI Use Cases Beyond Gaming"
07:13 "Detecting Abuse and Fraud"
13:19 Dynamic Model Orchestration Innovation
16:22 "Context-Aware AI for Conversations"
17:44 "Voice AI Transforming Customer Service"
22:49 AI Accountability and Compliance Challenges
25:36 AI, Customers, and Brand Trust
28:05 "Enhancing Communication Through AI"
Keywords:
Voice AI, voice native AI, voice understanding, tone detection AI, intent detection, emotional AI, prosody analysis, real-time fraud detection, synthetic voice detection, AI guardrails, deepfake detection, customer support AI, call analysis,
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