LangGraph
Open-source graph framework for durable, stateful AI agents
Overview
LangGraph is LangChain's open-source, low-level framework for building stateful AI agents with durable execution, streaming and human-in-the-loop control. A managed LangGraph Platform adds deployment, scaling and LangSmith observability on top.
Pricing
Pricing shown for reference only. These figures reflect RECATOOLS research as of 12 Jul 2026 and may be out of date or incomplete. This is not financial or purchasing advice — always confirm the current price on the provider’s official website before making any decision.
- 5,000 base traces/mo included
- 1 seat max
- Community support
- Pay-as-you-go overage
- 10,000 base traces/mo included
- Unlimited seats at $39 each
- 1 free dev-sized deployment
- 500 Fleet runs/mo included
- Email support
- Self-host or hybrid VPC deployment
- Custom SSO and RBAC
- SLA-backed support
- Annual invoicing
What you can produce with LangGraph
- Graph-based agent orchestration with explicit state machines
- Durable execution with automatic checkpointing and resume
- Human-in-the-loop interrupts mid-run
- Time-travel debugging via LangSmith traces
- Python and JavaScript/TypeScript SDKs
- Managed LangGraph Platform for deployment and autoscaling
- Streaming token and intermediate-step output
ASEAN Perspective
LangGraph in Southeast Asia
ASEAN-region availability and pricing notes coming soon. Drop the editorial team a note via /contact/ if you can supply local context (Singapore/Malaysia/Indonesia/Thailand/Vietnam).
LangGraph has genuine production mileage that most agent frameworks can only cite in a blog post: Klarna's customer-support assistant runs on it at 85 million users, Replit Agent's multi-step app-building flow is built on a multi-agent LangGraph architecture, and Uber's developer platform team used it to build code-review and test-generation agents credited with tens of thousands of saved engineer-hours. The 36k-plus GitHub stars and Python + JavaScript SDKs back that up.
The trade-off is the one r/LangChain regulars bring up constantly: this is a low-level graph library, not a batteries-included agent builder, and teams that want CrewAI-style speed to a working demo find LangGraph's explicit state machines slower to start with. That control is exactly why it holds up once a system gets messy — checkpointing, interrupts and time-travel debugging via LangSmith are built in, not bolted on. Free and MIT-licensed to self-host; the hosted Platform bills per node execution plus LangSmith seats.
What people say
LangChain's own published case studies are the strongest evidence LangGraph gets used past the demo stage. Klarna's AI assistant, built on LangGraph and LangSmith, handles support queries for its 85 million active users and reportedly cut resolution time by roughly 80%. Replit Agent — the tool that lets users generate and deploy full applications from a prompt — runs a multi-agent LangGraph architecture underneath, and its traces got complex enough (hundreds of steps per run) that the LangChain team had to rework LangSmith's ingestion just to render them. Uber's developer platform team built a suite of internal agents on LangGraph, including automated code-review and test-generation tools, and credits the effort with roughly 21,000 developer-hours saved and thousands of daily automated code fixes across a codebase touched by 5,000 engineers. Elastic uses it to orchestrate agents for real-time threat detection.
The recurring criticism, mostly visible on r/LangChain and in comparison posts, is abstraction overhead: LangGraph asks you to model your agent as an explicit graph of nodes and edges before you've written a line of business logic, and teams coming from simpler tools like CrewAI or Smolagents describe the ramp-up as slower. The counter-argument from teams that stuck with it is that the same explicitness — durable checkpointing, resumable state, human-in-the-loop interrupts — is what lets an agent survive a crash mid-task and pick up where it left off, which ad-hoc chains typically can't do cleanly.
On packaging: the core library is MIT-licensed and free to self-host indefinitely, in both Python and JavaScript. The managed LangGraph Platform bills separately — a Developer tier gives 100,000 free node executions a month before per-node charges kick in, Plus adds $39/seat LangSmith access plus deployment-minute charges for standby time, and Enterprise is negotiated case by case, with self-hosted-in-your-VPC or fully hybrid control-plane options for regulated teams that can't put agent traffic through a third-party cloud.
Summary of public user & expert reviews, compiled by RECATOOLS.
About this listing
This entry was compiled from publicly available data including LangGraph's official website, press releases, documentation, and reputable third-party publications. RECATOOLS is not affiliated with LangGraph unless explicitly stated.
Third-party AI tools update their pricing, features, availability, and policies frequently. Information here may be outdated by the time you read this — we make reasonable efforts to keep listings current, but cannot guarantee absolute accuracy.
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