LangGraph
AI / LLMFreemiumVisit Site
A low-level orchestration framework for building stateful, multi-step agent workflows with explicit control over state, branching, and human-in-the-loop steps.
Overview
LangGraph models an agent as a graph of nodes and edges rather than a single prompt loop, which gives engineering teams explicit control over state, branching, retries, and human approval steps. That control is exactly what enterprise agent workflows need — a multi-agent support system or a contract-review agent is a process, not a chat. It is a developer framework, not a no-code tool: expect to write real code and own your own deployment, observability, and evals. Pairs naturally with LangSmith for tracing.
Pros & Cons
Pros
- Explicit control over agent state and branching
- First-class human-in-the-loop and checkpointing
- Strong fit for durable, long-running workflows
- Large ecosystem and active development
Cons
- Requires real engineering investment
- Lower-level than no-code agent builders
- You own deployment and observability
Workflows that use LangGraph
Get a new AI workflow each week — many feature LangGraph and other tools in this category.