Kortix vs LangGraph: which open-source way to run stateful agents fits your team?

LangGraph is a low-level orchestration framework for building, managing and deploying long-running, stateful agents. Its own repository lists the primitives you get: durable execution that resumes a run after a failure, a human-in-the-loop hook that inspects and modifies state, short-term and long-term memory, and tracing through LangSmith. It is a library your engineers compose into an application, and the design is deliberately low-level: prompts, architecture and control flow stay your build.

That is the right shape when the agent runtime belongs inside your own code. Kortix handles the layer where the agents run. Kortix is the open-source AI Operating System: agents, their skills, your company memory and every connector live in one git repo you own, each session runs on its own cloud computer, and work reaches main through a change request a person approves. You can read and fork the source through Kortix on GitHub.

With a framework, you own the code and you carry the operation. The runtime, the sandbox, the secrets, the queue and the review step are yours to stand up and keep running, and LangGraph's own deployment story points at LangSmith Deployment, a separate product, for scaling stateful agents.

Kortix moves that half of the work into the platform. A session boots its own isolated machine and branch, connector credentials are brokered server-side so raw keys never reach the agent, and the audit log records every action. The configuration is text in a repo you own, so a teammate can read the history instead of trusting a black box.

Teams reach for a platform once the first prototypes have proved the idea and the questions change from how do we build this to who runs it, who approves it, and where the company's knowledge lives. The framework's flexibility is still there, but it is work you repeat for every agent, and the missing pieces are the shared ones: one place for memory, one review gate before work lands, and one set of permissions for people and agents.

LangGraph stays the better fit when the runtime must live inside your own application and you want to place every interrupt yourself. Kortix is the pick when you want the agents run, reviewed and governed for the whole company, with any model and your own keys. The Kortix vs CrewAI page walks the same decision for role-based agent teams, and Open-source AI agent platforms: how to choose one your team can own compares five platforms by ownership and deployment.