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LiveKit AgentsOpen-source framework for building real-time, multimodal voice and video AI agents.

4.5 (6)

Overview

LiveKit Agents is a developer framework for creating AI applications that interact with users in real time through speech, vision, and text. Built on top of LiveKit's WebRTC infrastructure, it handles the low-latency media plumbing needed for natural conversational experiences, letting developers focus on agent logic rather than streaming pipelines. The framework supports integrations with major speech-to-text, text-to-speech, and large language model providers, and it can orchestrate turn-taking, interruptions, and tool use. Typical use cases include voice assistants, AI phone agents, live tutors, customer support bots, and interactive avatars that can perceive their environment through audio and video.

Key features

  • Real-time voice, video, and text agent orchestration
  • WebRTC-based streaming infrastructure
  • Pluggable model providers for STT, LLM, and TTS
  • Built-in interruption and turn detection
  • Tool and function calling support
  • SDKs for Python and Node.js

Pricing

Model
Freemium
Rating
4.5 / 5 (6)

Use cases

Build Real-Time Voice Assistants

Create conversational voice assistants that handle natural turn-taking and interruptions, using pluggable STT, LLM, and TTS providers over a low-latency WebRTC pipeline.

AI Phone Agents for Customer Support

Deploy AI-powered phone agents that answer calls, resolve customer queries, and trigger backend actions through tool and function calling.

Interactive Live Tutors

Build multimodal tutoring agents that listen, speak, and see, enabling real-time back-and-forth instruction with students through voice and video.

Interactive AI Avatars

Power video-based avatars that perceive their environment via audio and vision, responding in real time for immersive conversational experiences.

Pros & Cons

Pros

  • Open source with permissive licensing
  • Low-latency real-time audio and video pipeline
  • Flexible integrations with major LLM, STT, and TTS providers
  • Handles interruptions and turn-taking out of the box

Cons

  • Requires developer expertise to deploy and customize
  • Self-hosting infrastructure adds operational overhead
  • Documentation can lag behind rapid feature updates

Reviews

4.5

Average from 6 ratings.

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Elena Rossi

Elena Rossi

Apr 6, 2026

Solid for our team

We rolled this out across the team last quarter and low-latency real-time audio and video pipeline. SDKs for Python and Node.js fits neatly into how we already work, and built-in interruption and turn detection removed a step we used to do by hand. but it has held up under daily use.

Esther Adeyemi

Esther Adeyemi

Dec 30, 2025

Does the job

Pretty happy overall. Tool and function calling support just works and flexible integrations with major LLM, STT, and TTS providers. Documentation can lag behind rapid feature updates can be annoying, but no dealbreakers — I'd recommend it to a friend without hesitating.

Kwame Mensah

Kwame Mensah

Dec 1, 2025

Does the job

Pretty happy overall. SDKs for Python and Node.js just works and handles interruptions and turn-taking out of the box. but no dealbreakers — I'd recommend it to a friend without hesitating.

Sofia Lindqvist

Sofia Lindqvist

Oct 31, 2025

Does the job

Pretty happy overall. Pluggable model providers for STT, LLM, and TTS just works and open source with permissive licensing. Self-hosting infrastructure adds operational overhead can be annoying, but no dealbreakers — I'd recommend it to a friend without hesitating.

Hannah Goldberg

Hannah Goldberg

Oct 15, 2025

Solid for our team

We rolled this out across the team last quarter and low-latency real-time audio and video pipeline. Tool and function calling support fits neatly into how we already work, and pluggable model providers for STT, LLM, and TTS removed a step we used to do by hand. but it has held up under daily use.

Daniel Schmidt

Daniel Schmidt

Jun 23, 2025

Skeptical, then convinced

I went in skeptical — most tools in this space overpromise. It actually delivers on sDKs for Python and Node.js, and handles interruptions and turn-taking out of the box caught me off guard. Requires developer expertise to deploy and customize is why this isn't a perfect score, still, I'd recommend giving it a real trial.

Q&A

How can I learn more?

This documentation site is organized into several main sections: Introduction: Start here to understand LiveKit's core concepts and get set up.Build Agents: Learn how to build AI agents using the LiveKit Agents framework.Agent Frontends: Build web, mobile, and hardware interfaces for agents.Telephony: Connect agents to phone networks and traditional communication systems.WebRTC Transport: Deep dive into WebRTC concepts and low-level transport details.Manage & Deploy: Deploy and manage LiveKit agents and infrastructure, and learn how to test, evaluate, and observe agent performance.Reference: API references, SDK documentation, and component libraries. Use the sidebar navigation to explore topics within each section. Each page includes code examples, guides, and links to related concepts. Start with Understanding LiveKit overview to learn core concepts, then follow the guides that match your use case.

Asked by Fumiko Sato · Nov 19, 2025

How does LiveKit work?

LiveKit's architecture consists of several key components that work together.

Asked by Yuki Kobayashi · Oct 31, 2025

What can I build?

LiveKit supports a wide range of applications: AI assistants: Multimodal AI assistants and avatars that interact through voice, video, and text.Video conferencing: Secure, private meetings for teams of any size.Interactive livestreaming: Broadcast to audiences with realtime engagement.Customer service: Flexible and observable web, mobile, and telephone support options.Healthcare: HIPAA-compliant telehealth with AI and humans in the loop.Robotics: Integrate realtime video and powerful AI models into real-world devices. LiveKit provides the realtime foundation (low latency, scalable performance, and flexible tools) needed to run production-ready AI experiences.

Asked by Ravi Chandrasekaran · Sep 20, 2025

Why use LiveKit?

LiveKit differentiates itself through several key advantages: Build faster with high-level abstractions: Use the LiveKit Agents framework to quickly build production-ready AI agents with built-in support for speech processing, turn-taking, multimodal events, and LLM integration. When you need custom behavior, access lower-level WebRTC primitives for complete control. Write once, deploy everywhere: Both human clients and AI agents use the same SDKs and APIs, so you can write agent logic once and deploy it across Web, iOS, Android, Flutter, Unity, and backend environments. Agents and clients interact seamlessly regardless of platform. Focus on building, not infrastructure: LiveKit handles the operational complexity of WebRTC so developers can focus on building agents. Choose between fully managed LiveKit Cloud or self-hosted deployment — both offer identical APIs and core capabilities. Connect to any system: Extend LiveKit with egress, ingress, telephony, and server APIs to build end-to-end workflows that span web, mobile, phone networks, and physical devices.

Asked by Chioma Nwosu · Sep 6, 2025

What is LiveKit?

LiveKit is an open source framework and cloud platform for building voice, video, and physical AI agents. It provides the tools you need to build agents that interact with users in realtime over audio, video, and data streams. Agents run on the LiveKit server, which supplies the low-latency infrastructure (including transport, routing, synchronization, and session management) built on a production-grade WebRTC stack. This architecture enables reliable and performant agent workloads.

Asked by Greta Nowak · Aug 9, 2025

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