LangGraph is a Python framework for building stateful, multi-actor agent workflows: primitives to define agents, their tools, and how they pass control between each other. It is a library you import and build on, and it is excellent for custom agent architectures - a graph of agents that pass messages, share state, and make decisions based on intermediate results. It is flexible, well-documented, and integrates with any LLM provider.

Farna Control is a self-hosted autonomous software factory on your infrastructure. It provides the complete factory floor for agentic software delivery: intake, agent dispatch, verification, human review, merge, release and evidence, with governance built in. Its formal category is an Agentic Delivery Governance platform, and its pipeline engine applies graph engineering to compose the factory's agents, tools, gates and humans.

Graph engineering: where the two overlap

Graph engineering is the 2026 industry term for designing agent systems as explicit graphs - networks of nodes (agents, tools, validators, humans) connected by edges (state, dependencies, message flow) - rather than a single agent loop. It is broader than any one framework.

LangGraph is a graph engineering framework. Farna Control is a software factory whose pipeline engine applies graph engineering to compose delivery work, its gates and its evidence. LangGraph builds custom graph architectures; Farna Control runs the broader factory around those graphs, including governance across your SDLC.

What LangGraph does not do

LangGraph provides no governance: no built-in gates, no human-in-the-loop review model, no append-only audit trail, no schema validation at agent boundaries, and no progressive autonomy model. You can build these on top of LangGraph, but you have to build them yourself.

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

How they relate

LangGraph and Farna Control are complementary, not competing. A team can use LangGraph to build a custom agent architecture and run it inside Farna Control, which provides the delivery system, governance, evidence and operational controls around the work.

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