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LangGraph

langchain.com

An open-source runtime and orchestration framework for controllable, stateful, and long-running AI agents.

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OVERVIEW

What is LangGraph?

LangGraph is an open-source runtime and orchestration framework for controllable, stateful, and long-running AI agents. It sits in the Automation & Agents category and is designed around app integration, workflow automation, and agent orchestration. Its main capabilities include graph-based agent workflows, persistent memory and checkpoints, human-in-the-loop controls.

The product is especially relevant for production agent systems, complex branching workflows, long-running applications. In practice, LangGraph can help users replace repetitive handoffs with a visible and reusable workflow. It works best as part of a reviewed workflow: start with a clear goal, provide useful context, assess the output, and refine it before relying on the result.

CORE FEATURES

What LangGraph can do

01

Graph-based agent workflows

Graph-based agent workflows is central to the LangGraph workflow, helping users begin with less setup and reach a workable first result faster.

02

Persistent memory and checkpoints

This capability makes LangGraph more useful for complex branching workflows, especially when several iterations are needed.

03

Human-in-the-loop controls

LangGraph combines this with graph-based agent workflows, so the output can remain connected to the wider task instead of becoming an isolated feature.

USE CASES

Where it fits best

Production agent systems

Use LangGraph for production agent systems when you want to replace repetitive handoffs with a visible and reusable workflow. Review the result against the original brief before sharing or publishing it.

Complex branching workflows

Use LangGraph for complex branching workflows when you want to apply persistent memory and checkpoints to a practical workflow. Review the result against the original brief before sharing or publishing it.

Long-running applications

Use LangGraph for long-running applications when you want to apply human-in-the-loop controls to a practical workflow. Review the result against the original brief before sharing or publishing it.

BEST FOR

Good fit

  • Production agent systems
  • Complex branching workflows
  • Long-running applications

NOT IDEAL FOR

Think twice if

  • Unmonitored workflows that can make irreversible changes
  • Processes with unclear ownership or frequently changing business rules

PROS

Reasons to try it

  • Brings graph-based agent workflows and persistent memory and checkpoints into one focused workflow.
  • Well aligned with production agent systems and complex branching workflows.
  • Offers an open-source route with more control over deployment.

CONS

Limits to consider

  • Self-hosting shifts setup, security, upgrades, and maintenance to the user.
  • Production automations need access controls, error handling, monitoring, and safe retry behavior.
  • Results depend on the quality of the input, context, and review process.

GETTING STARTED

How to try LangGraph

  1. 1

    Visit the official LangGraph website and review the current access and pricing options.

  2. 2

    Choose one small task related to production agent systems rather than testing the product with a vague request.

  3. 3

    Provide the relevant goal, source material, constraints, and desired output format.

  4. 4

    Try graph-based agent workflows, then refine the result using a second instruction or adjustment.

  5. 5

    Check the final output for accuracy, quality, permissions, and fit before putting it into production.

PRICING

Open source

An open-source option is available, although hosting, infrastructure, or managed cloud features can still create costs.

FAQ

Questions about LangGraph

What is LangGraph?+

LangGraph is a automation & agents product for app integration, workflow automation, and agent orchestration. An open-source runtime and orchestration framework for controllable, stateful, and long-running AI agents.

Is LangGraph free?+

An open-source option is available, although hosting, infrastructure, or managed cloud features can still create costs. Pricing and included limits can change, so confirm the latest details on the official website.

What is LangGraph best used for?+

LangGraph is best suited to production agent systems, complex branching workflows, long-running applications. Its strongest listed capabilities are graph-based agent workflows, persistent memory and checkpoints, human-in-the-loop controls.

Who should not use LangGraph?+

LangGraph may be a poor fit for unmonitored workflows that can make irreversible changes or processes with unclear ownership or frequently changing business rules. Production automations need access controls, error handling, monitoring, and safe retry behavior.

What are some LangGraph alternatives?+

Relevant alternatives in the same category include n8n, Zapier, Make. Compare them by workflow fit, output quality, integrations, usage limits, and current pricing.

Information is summarized from public product sources and written for comparison. Features, availability, and pricing may change. Last reviewed August 2026.