Dify is the fastest-growing open-source LLM application platform — providing a visual environment for building RAG pipelines, AI chatbots, agentic workflows and multi-step AI applications. We build and deploy Dify applications that deliver production AI capabilities without the overhead of building LLM infrastructure from scratch.
Dify is an open-source platform for building and operating LLM applications. Building directly with the OpenAI API requires coding the application layer, RAG infrastructure, prompt management, conversation history, API exposure and monitoring from scratch. Dify provides all these as a platform — reducing LLM application development time from weeks to days while maintaining the flexibility to customise with code.
Dify supports OpenAI (GPT-4o, GPT-3.5), Anthropic Claude, Google Gemini, Mistral, Llama and most major LLMs via API. Multi-model applications can use different models for different tasks — for example, a fast, cheap model for simple queries and a powerful model for complex reasoning.
Both options are available. Dify Cloud is fully managed with a free tier. Dify Community Edition can be self-hosted on your own infrastructure via Docker, giving complete data ownership and zero per-call pricing beyond your API costs. We recommend self-hosted for brands with data residency requirements or high-volume use cases where API cost management matters.
Dify's RAG pipeline takes your documents (PDFs, web pages, Notion exports, databases) and creates a vector knowledge base. When a user asks a question, Dify retrieves the most relevant document chunks and includes them in the LLM prompt — enabling the AI to answer questions based on your specific content rather than general training data.
Yes — Dify applications can be embedded in websites (chat widget), accessed via REST API from your applications or deployed as standalone web apps. Dify Cloud handles hosting for managed deployments. Self-hosted Dify runs in your own infrastructure for full production control.
Book a free Dify scoping session and design your LLM application architecture.