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Product comparison

Dify vs LangGraph

Choose Dify when the team wants an application-oriented AI workflow and agent builder. Choose LangGraph when engineers need graph-level control over agent state, branching, and orchestration.

Short answer: Dify is stronger as an AI application and workflow platform. LangGraph is stronger for engineering teams that need graph-based agent orchestration and control.

Agent Builders

Dify

Open-source LLM app and agent workflow platform covering agents, workflows, RAG, and application publishing.

Choose Dify when

  • The team wants a productized builder for internal AI applications.
  • Prompting, workflow setup, and deployment support matter more than framework-level control.
  • Non-framework users need to participate in building or operating AI workflows.
View product details dify.ai

Agent Builders

LangGraph

Graph-based agent orchestration framework for stateful, controllable agent workflows.

Choose LangGraph when

  • Engineers need explicit state graphs, branching, and agent control.
  • The team is comfortable building with code and framework primitives.
  • The agent workflow has complex orchestration requirements.
View product details www.langchain.com/langgraph

Shared fit

  • AI agent applications
  • Tool calling and workflow orchestration
  • Internal AI systems

Poor fit

  • Neither product is a simple consumer chatbot by itself.
  • A no-code builder may be too limiting for LangGraph-style engineering needs, while raw framework control may be too heavy for Dify-style application teams.

Sources

  • Dify official site: https://dify.ai/
  • LangGraph official site: https://www.langchain.com/langgraph

Need Check

Buyer context, data sources, deployment constraints, budget, and workflow depth can all change the answer.

If there is no strong fit, Recoo will say so.