It is a stateful orchestration framework designed to build and scale agentic applications that reliably handle complex tasks. LangGraph enables developers to create AI agents capable of automating real-world tasks through flexible control flows, including single-agent, multi-agent, hierarchical, and sequential workflows. It supports robust moderation and quality loops to ensure agents stay on track and provides tools for templatizing cognitive architectures, making it easy to configure tools, prompts, and models.
LangGraph facilitates seamless human-agent collaboration by allowing agents to draft actions for review and await approval before execution. Developers can inspect agent actions, “time-travel” to roll back decisions, and correct course as needed. It also bridges user expectations and agent capabilities with native token-by-token streaming and intermediate step streaming, enabling real-time visibility into agent reasoning and actions.
The LangGraph Platform offers APIs for crafting dynamic and interactive user experiences, deploying scalable infrastructure, and managing long-term memory for personalized interactions. It supports horizontally scaling servers, task queues, intelligent caching, and automated retries to handle large workloads gracefully. Developers can prototype, debug, and share agents using the visual LangGraph Studio and deploy applications with one-click SaaS or within their own VPC.
LangGraph is open-source under an MIT license, while the LangGraph Platform is proprietary, offering free and paid deployment options, including Self-Hosted Lite, Cloud SaaS, Bring Your Own Cloud (BYOC), and Self-Hosted Enterprise. It is trusted by companies across industries for building reliable, production-ready AI agents, with features like fault-tolerant scalability, dynamic APIs, and an integrated developer experience.
It is an all-in-one developer platform designed to support every phase of the lifecycle of LLM-powered applications, whether built with LangChain or not.
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