Choose LangChain if you want a choice of framework depth, from quick starts to low-level graph control, plus a separate platform for tracing, testing and monitoring. Choose CrewAI if role-based crews of agents match how you picture the work, or if business teams need a visual builder. Both have open source starting points, so it comes down to workflow shape and governance.
Picture the job you want an AI agent to do. Do you see it as a chain or graph of steps, with branches and loops you want to control yourself? Or do you see a small team, a researcher, a writer, a reviewer, each with a role, handing work to each other? That mental picture decides more of this choice than any feature list, and it's the first thing I'd settle with your developers.
For readability, I'll call LangChain the framework family and CrewAI the crew platform from here on.
Steps you wire up, or roles you assign
The framework family now offers three open source, model-agnostic frameworks for different needs. deepagents is for long-running work, the langchain library is for quick starts, and langgraph gives you low-level control over every step. You pick the depth that suits the project, and you can move between them.
The crew platform is built around three ideas: agents, crews and flows. Agents have roles, crews orchestrate them, and Flows add start, listen and router steps so you can control the order things happen in. Its docs describe a Python framework installed with uv that uses Pydantic for structured outputs. If your team already thinks in roles and hand-offs, that model will feel natural straight away.
Neither is just a library any more
Here's what's easy to miss if you last looked at these a while ago. The framework family's homepage doesn't sell one library. It sells an agent platform, where the three frameworks are open source options and LangSmith is the commercial layer for tracing, evaluation, deployment and monitoring. LangSmith also works with other frameworks, so you could use it even if you built your agents elsewhere.
The crew platform has made the same move. Its homepage leads with an enterprise build-and-runtime platform covering discovery, build, govern and optimise, with a visual builder, and the open source framework sits behind the Open Source and Docs links. So whichever you pick, you're choosing a vendor with a commercial platform, not only a GitHub project. That's worth knowing before your team falls in love with the free code.
Comparison grid
| Area | LangChain | CrewAI |
|---|---|---|
| Core abstraction | Three frameworks: deepagents, langchain and langgraph, from quick starts to low-level control | Role-based agents orchestrated as crews, with start, listen and router steps in Flows |
| Platform layer | LangSmith for tracing, evals, deployment and monitoring, with any framework | Enterprise platform covering discovery, build, govern and optimise, with a visual builder |
| Who builds | Code frameworks plus no-code Fleet agents for the whole company | No-code visual editor exportable to Python, plus a code-first API |
| Deployment | SaaS, BYOC or self-hosted | Cloud trial plus enterprise platform; local install via uv and the CLI |
| Governance | LLM Gateway with usage limits and sensitive data detection; human approval for sensitive actions | RBAC, immutable audit trails, human-in-the-loop gates, runtime hooks for PII redaction |
| Language | Model-agnostic open source harnesses | Python framework using Pydantic for structured outputs |
| Starting point | Free plan stated | Open source |
Governance and deployment for platform teams
If you're the person who'll get the call when an agent does something it shouldn't, this section matters most. The framework family offers an LLM Gateway that can set usage limits and detect sensitive data, and human approval for sensitive actions. You can run it as SaaS, bring your own cloud, or self-host.
The crew platform's governance list is longer on paper: role-based access control, immutable audit trails, human-in-the-loop gates and runtime hooks for PII redaction. It offers a cloud trial and an enterprise platform, and its docs show a local install through uv and the CLI. The vendor also says it's used by 65% of the Fortune 500, which is a marketing claim rather than something you can check.
On no-code, both have something. The crew platform's visual editor exports to Python, which is handy if a business user sketches an agent and a developer takes it on. The framework family mentions no-code Fleet agents for the whole company alongside its code frameworks.
Other agent frameworks to consider
If neither feels right, these three are the closest rivals. Our wider list of the best AI agent frameworks covers more.
LlamaIndex
Best for: Agents that live on documents: it's now centred on LlamaParse for parsing, extraction and indexing, plus LiteParse, a fast local open source parser.
Haystack
Best for: Python teams after an open source orchestration framework installed with pip, with an optional enterprise platform and support offering.
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AutoGen
Best for: Prototyping multi-agent apps, with AgentChat for conversational agents, Core for event-driven systems and Studio as a no-code web UI.
Final verdict for developers and team leads
Go with the framework family if you want to choose your own depth, from quick templates to low-level graph control, and you want a separate platform for tracing, evaluation and monitoring that isn't tied to one framework. Go with the crew platform if role-based crews match the way you think about the work, or if business teams need a visual builder with audit trails and access controls. Both start open source, so you don't need to commit before you've built something small in each.
If you're still weighing up other routes, our page of alternatives to CrewAI is worth a look.
Do you make an AI agent framework? Tool makers can ask to be considered for a featured place on this page.
Want your tool on this list? Featured spots and reviews here are paid partnerships. Here's how to partner with me.
Frequently asked questions
Is LangChain the same thing as LangGraph?
No. The framework family now offers three open source frameworks: langchain for quick starts, langgraph for low-level control and deepagents for long-running work. LangSmith is the platform that sits on top.
Is CrewAI open source?
The core framework is open source and written in Python. The vendor also sells an enterprise platform with a visual builder and governance tools.
Can I use LangSmith with a different framework?
Yes. LangSmith is described as framework-agnostic, so it can trace, evaluate and monitor agents built elsewhere.
Which one suits non-developers?
The crew platform has a no-code visual editor that exports to Python. The framework family mentions no-code Fleet agents for the whole company.
Can I self-host either one?
The framework family lists SaaS, bring-your-own-cloud and self-hosted options. The crew platform's docs describe a local install, and it also offers a cloud trial and an enterprise platform.
