What is LiveKit?

LiveKit handles the hard parts of running real-time voice infrastructure: low-latency audio transport (typically WebRTC under the hood), SIP integration for telephony, turn detection (deciding when a participant has finished speaking), interruption handling (gracefully stopping playback when someone talks over the agent), and cross-platform client SDKs (web, iOS, Android, Python, Node).

For AI agents specifically, LiveKit ships an Agents framework that wires up STT providers (Deepgram, Whisper), LLM providers (OpenAI, Anthropic, Gemini), and TTS providers (ElevenLabs, Cartesia, OpenAI) into a single agent loop. Builders write the system prompt and tool functions; LiveKit handles the rest.

LiveKit, Vapi, and Retell occupy similar positions in the voice AI infrastructure stack but differ in approach. LiveKit is the most foundational — it’s an open-source primitive (real-time audio infrastructure) with an Agents framework on top. Vapi is a higher-level platform optimized for conversational agents specifically. Retell is a developer-friendly platform with strong defaults and a polished SDK. All three are reasonable choices; the right pick depends on how much customization the deployment needs.

Hodos360’s reference deployment at Vasquez Law Firm uses LiveKit + LangGraph because we wanted maximum control over agent behavior and routing. Other production deployments do well on Vapi or Retell.

In the Hodos360 / Vasquez Law Firm stack, LiveKit handles SIP termination from CallRail, manages the real-time audio loop with Deepgram (STT) and ElevenLabs (TTS), and coordinates with LangGraph for agent state management. The agent processes English and Spanish in the same conversation without requiring a hand-off, which is one of the design constraints LiveKit handles cleanly.