Modulo vs LangGraph: what's the difference?

LangGraph is a Python framework for building stateful, multi-actor agent workflows. It gives you the primitives to define agents, their tools, and how they pass control between each other. It is a library you import and build on top of.

Modulo is a self-hosted platform for governing agent-powered software delivery. It gives you a complete pipeline model with triggers, agent dispatch, deterministic gates, human review, audit trails, and progressive autonomy. It is a platform you deploy and configure.

What LangGraph does well

LangGraph is excellent for building custom agent architectures. If you need a graph of agents that pass messages, share state, and make decisions based on intermediate results, LangGraph gives you the building blocks. It is flexible, well-documented, and integrates with any LLM provider.

What LangGraph does not do

LangGraph does not provide governance. There are no built-in gates, no human-in-the-loop review model, no immutable audit trail, no schema validation at agent boundaries, and no progressive autonomy model. You can build these things on top of LangGraph, but you have to build them yourself.

LangGraph is also not a platform. It is a library. You need to host it, manage its state, handle scaling, and build the surrounding infrastructure. This is appropriate for teams with the engineering capacity to build their own platform, but it is a significant investment.

How they relate

LangGraph and Modulo are not direct competitors. LangGraph is a framework for building agent systems. Modulo is a platform for governing agent SDLCs. A team could use LangGraph to build a custom agent and then run that agent inside a Modulo pipeline, where Modulo provides the governance layer around it.

The difference is the level of abstraction. LangGraph operates at the agent-architecture level. Modulo operates at the SDLC-governance level. They are complementary, not competing.

The principle behind this: we dispatch, we don't run agents - Modulo dispatches work to the runtimes you already use, and owns everything around the work.