LiveKit real-time video is a developer-friendly stack for building real-time video, audio, and data experiences using WebRTC. If you’re building AI agents that can join calls, live copilots, voice assistants, or multi-user streaming apps, LiveKit gives you the infrastructure layer: an SFU server, client SDKs, and production features like auth, TURN, and webhooks.
TL;DR
- LiveKit is an open-source, scalable WebRTC SFU (selective forwarding unit) for multi-user conferencing.
- It ships with modern client SDKs and supports production needs: JWT auth, TURN, webhooks, multi-region.
- For AI apps, it’s a strong base for real-time voice/video agents and copilots.
Table of Contents
- What is LiveKit?
- Key features (SFU, SDKs, auth, TURN)
- Use cases (AI voice/video agents)
- Reference architecture
- Getting started
- Tools & platforms (official + GitHub links)
- Related reads on aivineet
What is LiveKit?
LiveKit is an open-source project that provides scalable, multi-user conferencing based on WebRTC. At its core is a distributed SFU that routes audio/video streams efficiently between participants. Around that, LiveKit provides client SDKs, server APIs, and deployment patterns to run it in production.
Key features (SFU, SDKs, auth, TURN)
- Scalable WebRTC SFU for multi-user calls
- Client SDKs for modern apps
- JWT authentication and access control
- Connectivity: UDP/TCP/TURN support for tough networks
- Deployment: single binary, Docker, Kubernetes
- Extras: speaker detection, simulcast, selective subscription, moderation APIs, webhooks
Use cases (AI voice/video agents)
- Real-time voice agents that join calls and respond with low latency
- Meeting copilots: live transcription + summarization + action items
- Live streaming copilots for creators
- Interactive video apps with chat/data channels
Reference architecture
Clients (web/mobile)
-> LiveKit SFU (WebRTC)
-> Webhooks / Server APIs
-> AI services (ASR, LLM, TTS)
-> Storage/analytics (optional)Getting started
Start with the official docs and demos, then decide whether to use LiveKit Cloud or self-host (Docker/K8s). For AI assistants, the key is designing a tight latency budget across ASR → LLM → TTS while your agent participates in the call.
Tools & platforms (official + GitHub links)
- LiveKit (official): livekit.io
- Docs: docs.livekit.io
- LiveKit (GitHub): github.com/livekit/livekit
- Pion WebRTC: github.com/pion/webrtc