Google Cloud AI outlines voice agent production architecture

Building a production-ready voice agent requires navigating three architectural layers: raw API constraints, transcript processing logic, and telephony requirements. Sergio Villani and Pedro Melendez of Google Cloud AI explain that while speech-to-speech models like Gemini 3.8 Live reduce latency by combining transcription and reasoning, building a text-based pipeline demands careful handling of API gaps, decoupling interim and finalized transcripts, and managing hybrid voice activity detection alongside telephony. Open article →