If your voice AI system can touch real systems or trigger actions with business consequences, your approach to AI agent tool calling security matters. When voice AI agents can modify customer data, trigger escalations, update ticketing systems, or execute workflows—especially for customer service in regulated industries like
LLMs alone can’t “act.” They generate text. The key to success, and the way to avoid the 80% of AI projects that never leave the prototype stage, is moving beyond conversation to orchestration. This means integrating LLM reasoning with automation frameworks, enabling explainable outcomes and human oversight,
Earlier this month, our CTO Alberto Gonzalez and I descended upon Las Vegas for AWS re:Invent 2025. As an AWS Partner working daily with AWS services to build real-time voice, video, and AI systems, re:Invent is more than a conference for us. It’s a chance to validate
The choice between conversation-based and turn-based Voice AI agent patterns is a strategic business decision, not just a technical detail. Beyond what your agent will say, you must decide how it will run. This architectural choice defines how your voicebot will scale, what it will cost to
