From Cascades to Streams: Voice Agents for Real-Time Conversations

Traditional voice agents built on cascaded pipelines (STT → LLM → TTS) introduce cumulative latency that drives user churn in real-time applications. Sarvam AI and Swiggy demonstrate that native audio streaming with sub-second response times—powered by Indic-native models and bidirectional WebSocket architecture—is essential to scale for the next billion users. This architectural shift from request-response to streaming state machines represents a fundamental reimagining of how conversational AI must be built for markets where milliseconds determine success or failure.