Why WebRTC beats WebSockets for realtime voice AI

When building voice AI agents, developers face crucial architectural decisions regarding audio transport, often opting for WebSockets due to their familiarity, despite their inadequacy in handling real-time media. WebSockets, designed for structured data, struggle with real-time audio due to TCP's properties like head-of-line blocking, which introduces delays that disrupt conversational flow. In contrast, WebRTC, built specifically for real-time communication, uses UDP to provide loss tolerance and consistent timing, making it more suitable for voice interactions. It includes built-in jitter buffers, media-aware congestion control, and codec negotiation, all of which enhance audio delivery without the need for complex custom solutions. Additionally, using an SFU (Selective Forwarding Unit) within WebRTC infrastructures allows efficient media routing and adaptation to varied network conditions, critical for scaling voice AI globally. This architecture, exemplified by platforms like LiveKit, enables developers to focus on innovating their AI agents rather than reinventing foundational real-time audio solutions, ensuring high-quality, responsive user experiences across diverse network environments.

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