LangGraph is an agent runtime and low-level orchestration framework from the LangChain team, positioned around balancing agent control with agency. It uses graph-based primitives to build customizable single-agent, multi-agent, and hierarchical control flows, with memory, human-in-the-loop checks, persistence, and production deployment patterns for reliable agent systems.
Features
- Graph-based agent orchestration
- State and persistence
- Human-in-the-loop controls
- Multi-agent and hierarchical flows
- Built-in memory
- Production deployment patterns
Use Cases
- Reliable agent workflows
- Multi-step task orchestration
- Human-approved agents
- Recoverable execution flows
- Multi-agent systems
- Enterprise agent prototype-to-production
FAQ
LangGraph is an agent runtime and low-level orchestration framework from the LangChain team, positioned around balancing agent control with agency. It uses graph-based primitives to build customizable single-agent, multi-agent, and hierarchical control flows, with memory, human-in-the-loop checks, persistence, and production deployment patterns for reliable agent systems. Core capabilities include: Graph-based agent orchestration, State and persistence, Human-in-the-loop controls.
Common scenarios include: Reliable agent workflows, Multi-step task orchestration, Human-approved agents.
Related Guides
Agents & Frameworks
Best AI Agent Tools in 2026
Compare AI agent tools for research, automation, office work, local workflows, multi-agent collaboration, and internal agent apps.
View guideAgents & Frameworks
Best AI Agent Frameworks in 2026
Compare AI agent frameworks for building controllable AI agents, RAG systems, tool-using workflows, multi-agent apps, and production LLM products.
View guide
