Build a Voice AI Application With Twilio ConversationRelay and BentoML

Building a voice AI application traditionally requires managing components such as speech-to-text, text-to-speech, real-time streaming, and large language models. However, using Twilio ConversationRelay and BentoML simplifies this process by handling critical features like STT, TTS, real-time streaming, and interruption handling. With ConversationRelay, the voice interaction layer is managed, and BentoML helps handle model serving, application packaging, and production deployment. The framework automates hosting and deployment of a WebSocket server, enabling seamless real-time communication between Twilio and the LLM. It also allows developers to easily switch between different LLMs for testing or deploying updates in production. By combining ConversationRelay and BentoML, users can build a production-ready voice AI application with customizable serving logic, interruption handling, streaming responses, and scalable deployment in the cloud.