Who LiveKit is for#
AI product teams building voice agents
Use LiveKit Agents when the agent must talk, listen, interrupt politely, and share state with a web or mobile client in realtime.
Skip if:
Skip if your workflow is asynchronous support chat or batch content generation.
Developers adding phone-based AI workflows
The SIP integration path makes it suitable for inbound or outbound calling experiences where the AI participant needs model tools and call audio.
Skip if:
Skip if you need a call-center suite with workforce management and reporting out of the box.
The problem it solves#
Realtime AI agents break down when the media layer, speech pipeline, model calls, and client experience all live in separate systems. Teams often start with a chat API, then discover they need WebRTC rooms, phone calls, interruption handling, and a way to route users to server-side agents. The result is a fragile stack where latency and handoff bugs damage the conversation experience.
How it solves it#
Realtime agent participants
Runs programmable server-side participants inside LiveKit rooms, so an AI agent can join a session like any other audio or video participant.
Speech and model integrations
Connects STT, LLM, TTS, realtime APIs, and turn detection plugins from one agent framework instead of a custom glue layer.
Telephony and client data support
Works with LiveKit SIP, RPC, and data APIs, which lets agents place or receive calls and exchange structured events with client apps.
Strengths and trade-offs#
Strengths
- Built for low-latency mediaThe framework sits on LiveKit WebRTC infrastructure, so voice and video interaction are first-class parts of the agent instead of an add-on to text chat.
- Apache-2.0 agent frameworkThe repository is Apache-2.0, which gives teams a permissive base for commercial agent applications and self-hosted deployments.
Trade-offs
- -Realtime systems require infrastructure disciplineVoice agents need media servers, model provider keys, job dispatch, and latency monitoring. A simple chatbot platform is easier if your product only needs text.
Install and self-host#
Install the Python agent framework in a virtual environment, then connect it to your LiveKit deployment and model providers.
```bash
pip install "livekit-agents[openai,silero,deepgram,cartesia,turn-detector]"
```What it's built on#
- Languages
- Python
FAQ#
Is LiveKit Agents open source?
Yes. The LiveKit Agents repository is Apache-2.0 licensed, and the README points to self-hosting the wider LiveKit stack.
Can LiveKit Agents handle voice instead of text only?
Yes. The framework is built for realtime voice and multimodal agents with STT, TTS, LLM, and turn-detection integrations.
Is LiveKit Agents a replacement for Twilio?
It can replace parts of a paid realtime media or telephony stack when you want control over the WebRTC and agent layer. Twilio may still fit teams that only want managed phone infrastructure.
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