Code-first agent development
Build agents with LiveKit's open source SDKs in Python or TypeScript, then write the agent logic directly in code.
LiveKit
Freemium
LiveKit é uma plataforma open source para desenvolvedores criarem, implantarem e observarem agentes de IA de voz, vídeo e físicos com Python ou TypeScript, usando o LiveKit Cloud em produção.
O que é LiveKit?
LiveKit is an open source framework and developer platform for building voice, video, and physical AI agents. It is positioned for teams that want to create agent experiences in code, deploy them to cloud infrastructure, and observe behavior in production.
The product combines SDKs, cloud deployment, telephony support, and realtime observability in one platform. The source highlights Python and TypeScript agent development, global infrastructure, and support for agent sessions, routing, scaling, and telemetry across live conversations.
O que LiveKit pode fazer?
Cloud deployment and scaling
Deploy agents to LiveKit Cloud so the runtime infrastructure, routing, and autoscaling are handled by the platform.
Production observability
Monitor conversations in production with realtime observability and session metrics, including telemetry for agent sessions.
Inference gateway for voice workflows
Use the platform's model and speech stack to connect LLM, STT, and TTS providers through the agent workflow.
Multichannel voice delivery
Connect agents to web, mobile, and phone experiences, including telephony and SIP-based workflows.
Build, test, and ship lifecycle support
Test and iterate against real scenarios before shipping, with tooling for agent backend, frontend, and testing workflows.
Casos de uso
“Production voice agents”
Create a voice assistant in Python or TypeScript, connect it to STT, LLM, and TTS providers, and run the agent in a production workflow.
“Web and mobile conversational apps”
Build agent experiences that run in a browser or mobile app, where the user speaks and the agent responds in realtime.
“Telephony-enabled assistants”
Add phone-call workflows to an agent so it can place or receive calls through telephony integrations.
“Managed production deployment”
Deploy agents on cloud infrastructure with routing and autoscaling handled by LiveKit Cloud for teams that do not want to manage runtime operations.
“Operational observability”
Track live sessions and conversation behavior in production so teams can inspect agent performance after launch.
Perguntas frequentes
How do you build and deploy agents with LiveKit?
LiveKit is built to let you build agents in Python or TypeScript, then deploy them to LiveKit Cloud and observe conversations in production.
What kinds of agents does LiveKit support?
The source describes LiveKit as a platform for voice AI, video AI, and physical AI agents, with agent infrastructure and realtime observability.
Does LiveKit have free and paid plans?
The pricing page shows a free Start for free option, paid Build, Ship, and Scale plans, and an Enterprise option that requires contacting sales.
Is LiveKit aimed at developers or non-technical users?
The platform emphasizes open source SDKs, cloud deployment, telephony, and observability rather than a no-code workflow.
What integrations are documented in the source?
The source does not list a fixed feature-by-feature integration catalog, but it does mention model integrations, telephony, SIP, and deployment on LiveKit Cloud.
Informações rápidas
- Category
- Developer Tool
- Primary use
- Build, deploy, and observe voice AI agents
- Supported languages
- Python and TypeScript
- Deployment
- LiveKit Cloud
- Source domain
- livekit.io
- Pricing model
- Free start plan with paid Build, Ship, Scale, and Enterprise options
Análise de tráfego de LiveKit
Os dados de tráfego são apenas para referência.
- Classificação do domínio
- 79
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