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LangChain

LangChain

Framework for building LLM apps.

Free planFrom $39/moCode & DeveloperAI Agents
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About LangChain

Picture the agent you built last week. It worked fine on your laptop, called the right tools, returned sensible answers. Then you put it in front of real traffic and it started looping, picking the wrong tool, or burning tokens on a task that should take three steps. LangChain's pitch is built around that exact moment. You write the agent with one of its open source frameworks, then you use LangSmith to see what it's actually doing, score how well it's doing it, and ship it to production without stitching together five separate vendors.

The open source side is where most people start. The langchain library is the quick start option that works "with any model provider," langgraph gives you "low-level control" when you need to define the agent's flow yourself, and deepagents targets "long-running agents for complex tasks." The numbers suggest you won't be alone: the company claims 350M+ monthly open source downloads, 7K+ active LangSmith customers, and 5 of the Fortune 10 on LangSmith. The paid platform is the commercial layer on top. Observability shows traces of every step, Evaluation scores agent performance, Deployment handles shipping and scaling, Sandboxes run agent-generated code safely, and an LLM Gateway controls model calls. There's also Fleet, a no-code option pitched as "agents for the whole company."

The honest catch is that this is a platform play, and the product list has grown long. If you just want a thin wrapper around an LLM API, it's more than you need. Pricing is per seat plus pay-as-you-go on traces, starting at $0 for one developer and $39 per seat on Plus, so costs grow with both team size and agent traffic. If you're running agents in production and you're tired of guessing why they fail, it's one of the most complete options you'll find, and the free tier is enough to find out whether the tracing alone earns its keep.

Key features

Open source agent frameworks

You can pick between langchain for quick starts with any model provider, langgraph for low-level control over agent flow, and deepagents for long-running agents that handle complex tasks.

LangSmith Observability

Observability traces each step your agent takes so you can see exactly which tool calls and model responses led to a bad output.

LangSmith Evaluation

Evaluation lets you score agent performance over time, which gives you a way to tell whether a prompt or model change actually helped.

Deployment and Sandboxes

Deployment is built to ship and scale agents in production, while Sandboxes give agent-generated code an isolated place to run safely.

LLM Gateway

The LLM Gateway sits between your agents and model providers so you can control which model calls go out.

Fleet no-code agents

Fleet is the no-code piece of the platform, aimed at letting people outside the engineering team build and use agents across the company.

Best for

  • engineering teams running agents in production
  • developers already building on langchain or langgraph
  • teams that need tracing and evals in one place
  • enterprises that require self-hosted or hybrid deployment
  • solo builders prototyping agents on a free tier

Skip if

  • Skip this if you only need a single LLM API call with no tools or multi-step logic, since the frameworks and platform add layers you won't use.
  • Skip this if you need predictable flat-rate billing, because every paid plan is per seat plus pay-as-you-go on traces.
  • Skip this if you need self-hosting on a small budget, as self-hosted and hybrid options are only listed on the custom-priced Enterprise plan.

Pros & cons

Pros

  • The open source frameworks are free and huge in adoption, with the company citing 350M+ monthly downloads, so examples and community answers are easy to find.
  • You get build, trace, evaluate, and deploy under one account instead of stitching separate tools together.
  • The Developer plan costs $0 and includes 5k base traces a month, which is plenty to see whether tracing pays off before spending anything.
  • Plus lets you add unlimited seats at $39 per seat, so you aren't forced into a sales call just to grow the team.
  • Enterprise covers the security checklist items larger companies ask for: custom SSO, ABAC, and RBAC.

Cons

  • Costs scale on two axes, seats and traces, so a team with high agent traffic can climb well past $39 per seat once it exceeds the included 10k base traces.
  • The free Developer plan is capped at 1 seat with community support only, so even a two-person team needs Plus.
  • Deployment and the Agent Improvement Engine are gated to Plus, which means the free tier is mostly an observability trial.
  • The product lineup is sprawling: LangSmith Platform, Observability, Evaluation, Deployment, Fleet, Sandboxes, LLM Gateway, plus three frameworks, and the homepage doesn't explain how they fit together.

Pricing

TierPriceIncludes
Developer$0 / seat per month, then pay as you go1 seat, up to 5k base traces per month, community support
Plus$39 / seat per month, then pay as you goUp to 10k base traces per month, access to Deployment, Engine and more, unlimited seats
EnterpriseCustom pricing, then pay as you goSelf-hosted and hybrid deployment options, custom SSO, ABAC and RBAC

Frequently asked questions

Is LangChain free?

The langchain, langgraph, and deepagents frameworks are open source. The LangSmith platform has a $0 Developer plan with 1 seat and up to 5k base traces a month, then pay-as-you-go.

What's the difference between LangChain and LangSmith?

LangChain is the open source framework you write agents with, while LangSmith is the paid platform for observability, evaluation, and deployment. You can use LangSmith to trace agents, and you don't have to be on the free tier forever to use the frameworks.

What do I get on the $39 Plus plan?

Plus costs $39 per seat per month and includes up to 10k base traces a month, then pay-as-you-go. It adds access to Deployment and the Agent Improvement Engine, and you can add unlimited seats.

Can I self-host LangSmith?

Self-hosted and hybrid deployment options are listed only on the Enterprise plan, which uses custom pricing. That plan also adds custom SSO, ABAC, and RBAC.

Should I use langchain or langgraph?

langchain is positioned as the quick start option that works with any model provider, while langgraph is for when you want low-level control over the agent's flow. For long-running, complex tasks, the company points you to deepagents instead.

How LangChain compares

LangChain vs LlamaIndex

LlamaIndex is the stronger pick if your app is mainly retrieval over your own documents, while LangChain makes more sense when you need multi-step agents plus tracing and deployment in one account.

LangChain vs CrewAI

CrewAI is quicker for role-based multi-agent prototypes, but langgraph gives you finer control over flow and LangSmith gives you production tracing that CrewAI users usually bolt on separately.

LangChain vs Langfuse

Langfuse is a solid open source choice if all you want is LLM tracing you can host yourself, whereas LangSmith only offers self-hosting on Enterprise but bundles evaluation, deployment, and sandboxes alongside it.

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