The Chanl Blog
Insights on building, connecting, and monitoring AI agents for customer experience — from the teams shipping them.
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235 articles · Page 18 of 20
The Evolution of Voice Synthesis: Beyond Natural Sounding to Emotionally Intelligent
Industry research shows that 70-75% of enterprises are moving beyond basic voice synthesis to emotionally intelligent systems. Discover how voice AI is evolving from natural-sounding to emotionally aware.
Automated QA Grading: Are AI Models Better Call Scorers Than Humans?
Industry research shows that 75-80% of enterprises are implementing AI-powered QA grading systems. Discover whether AI models actually outperform human call scorers and how to implement effective automated grading.
Conversational Analytics Gone Wrong: Top Pitfalls in Call Data Interpretation
Industry research shows that 70-75% of enterprises misinterpret conversational AI analytics, leading to costly business decisions. Discover the most common pitfalls and how to avoid them.
How callers actually think about AI — and where every assumption breaks
Industry research reveals that 60-65% of callers develop incorrect mental models of AI systems. Discover how understanding caller psychology transforms voice AI design and reduces frustration.
Agentic AI Liability: Who's Responsible for What When Things Go Wrong?
Industry research shows that 80-85% of enterprises lack clear liability frameworks for agentic AI failures. Discover how to establish responsibility structures that protect your organization while enabling AI innovation.
70% of Enterprises Are Ripping Out Their IVRs. Here's Why, and What Replaces Them
Industry research shows that 70-75% of enterprises are phasing out IVRs in favor of conversational AI. Here's how to build transitions that preserve customer experience while modernizing operations.
Conversation as a Service: Will the Next SaaS Giants Be Voice-First?
Voice-first SaaS is generating real revenue but not in the way most people predicted. Here's an honest look at what's working, what's hype, and whether conversation platforms will produce the next generation of software giants.
How LLMs Changed Agent Training Forever: From Writing Rules to Writing Prompts
LLMs didn't just improve agent training. They changed the entire discipline. Here's what actually shifted, what works in production, and what the industry still gets wrong.
Prompt engineering vs. context engineering: What's the next step for voice AI?
While prompt engineering focuses on perfecting inputs, context engineering optimizes the entire conversation environment. Discover why context engineering is becoming the key differentiator in voice AI.
Digital Twins for AI Agents: Simulate Before You Ship
Build digital twins that test your AI agent against thousands of synthetic customers. Architecture, TypeScript code, and the patterns that catch failures.
Silent Monitoring by AI: Quality Assurance Without Human Eavesdropping
Industry research shows that 70-75% of enterprises are implementing AI-powered silent monitoring for quality assurance. Discover how automated QA transforms agent performance without privacy concerns.
Failure Modes: What 'Accidents' in Voice AI Teach Us about Responsible Deployment
When voice AI systems fail, they don't just break. They reveal fundamental truths about how we build, deploy, and trust artificial intelligence. Discover what real-world failures teach us about responsible AI.
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