LangGraph is a low-level, graph-based orchestration framework built by LangChain for creating stateful, multi-agent AI systems. Unlike traditional linear chains, LangGraph models workflows as directed graphs where nodes represent actions (LLM calls, tool executions, or logic) and edges define transitions between them. This architecture enables cycles, conditional routing, human-in-the-loop patterns, and persistent state management — making it ideal for building production-grade agents that need to handle complex reasoning, error recovery, and long-running conversations. LangGraph's explicit control flow gives developers fine-grained control over agent behavior, while built-in checkpointing and time-travel debugging capabilities ensure reliability and debuggability at scale.