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Dify

Visual platform for building agentic workflows, RAG pipelines, and LLM-powered apps. Supports hundreds of models, MCP integration, and self-hosted deployment.

Open Source Alternative to:

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Dify is an open source platform for building production-ready AI applications without writing boilerplate infrastructure. It targets developers and teams who want to move from idea to deployed app quickly, using a visual workflow builder rather than assembling everything from scratch.

The core of Dify is its agentic workflow builder: a drag-and-drop canvas where you connect LLM calls, tools, conditional logic, and data sources into multi-step pipelines. These aren't toy demos. The platform is designed to handle real production traffic, with enterprise-grade security and scalability built in from the start.

Key capabilities include:

  • RAG pipelines: ingest documents, connect knowledge bases, and make your data queryable by any LLM with minimal setup
  • Multi-model support: connect to hundreds of global LLMs, including OpenAI, Anthropic, and locally-hosted models via Ollama or OpenAI-compatible APIs
  • MCP integration: native support for the Model Context Protocol, both consuming external MCP servers and publishing your own app as an MCP server
  • Plugin marketplace: extend functionality with community plugins without touching source code
  • Observability: built-in monitoring so you can iterate based on real usage data

Teams can self-host the entire platform, which matters for organizations with strict data residency or compliance requirements. The no-code interface makes it accessible to non-engineers, while the underlying API and plugin system give developers room to build complex, custom logic.

Dify is used across industries from biomedicine to automotive. Ricoh built internal tooling on it; Volvo Cars uses it for rapid AI validation. Over a million applications run on Dify deployments worldwide.

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