Visual workflow builder
Build AI apps and workflows with a drag-and-drop interface so teams can move from idea to implementation without assembling every piece manually.
Dify
Dify is an agentic workflow builder to create, deploy, and manage AI apps, agents, and RAG pipelines in cloud or self-hosted setups.
What Dify is
Dify is an agentic workflow builder for developing, deploying, and managing autonomous agents, RAG pipelines, and related AI applications. The homepage positions it as a way for teams to build production-ready agentic workflows with a visual interface and supporting backend services.
The product combines workflow design, model selection, retrieval-augmented generation, tools, integrations, and observability in one platform. The site also frames Dify for different deployment and buying contexts, including cloud service, self-hosted community edition, education, partner, and enterprise use.
Pricing information shows a free Sandbox tier, paid Professional and Team plans, and a contact-sales path for enterprise needs. The education page adds a free option for students and educators and a self-hosted community edition for controlled campus deployment.
Core capabilities
Multi-model LLM support
Work with global large language models and compare performance across open-source and proprietary providers, including options listed on the pricing page.
RAG pipeline support
Connect data sources into RAG pipelines by extracting, transforming, and indexing information into vector databases for LLM use.
MCP-based integrations
Link external APIs, databases, and services through native MCP integration, including support for HTTP-based MCP services with pre-authorized and auth-free modes.
Tools and publishable agents
Expand applications with tools and plugins, then publish workflows or agents as a standard MCP server for use across MCP clients.
Operational support for production apps
Use the platform’s observability and backend-as-a-service approach to manage production workflows without building every operational layer from scratch.
Where Dify fits
Teams building production AI apps
Build agentic applications with a visual workflow that can be deployed and managed from the same platform, rather than stitching together separate tools for orchestration and operations.
RAG and knowledge retrieval projects
Prepare internal knowledge assistants by extracting source data, transforming it, and indexing it into vector databases for RAG-based retrieval.
Integrations with business systems
Connect existing services through MCP, APIs, databases, and plugins when the AI application needs to interact with external systems.
Education and campus deployment
Use the cloud service for quick setup, or choose the self-hosted community edition when the requirement is controlled on-campus deployment.
Small teams validating an AI product
Start with the free Sandbox or a lower-tier paid plan, then move up as app count, team size, message volume, or workflow throughput increases.
Pros and Cons
Pros
- Supports a broad workflow that covers app building, RAG pipelines, integrations, tools, and observability in one platform.
- Offers multiple deployment and buying paths, including free Sandbox access, paid cloud plans, education access, self-hosted community edition, and enterprise contact-sales options.
- Lets users work with several model providers, including OpenAI, Anthropic, Llama2, Azure OpenAI, Hugging Face, and Replicate.
- Provides native MCP integration and can publish workflows or agents as standard MCP servers, which can simplify cross-tool use.
Cons
- The public site gives only partial detail on the full integration catalog and supported outputs, so some implementation questions still require documentation review.
- The pricing page is detailed on tiers and limits, but enterprise pricing is not listed publicly and requires contact with sales.
FAQ
Who is Dify for?
Dify is built for teams that want to design, deploy, and manage agentic workflows, RAG pipelines, and AI applications from one platform. The source also shows plans for students and educators, independent developers and small teams, medium-sized teams, and enterprise buyers.
Does Dify have free and paid options?
The pricing page shows a free Sandbox tier, paid Professional and Team plans, and a contact-us flow for enterprise options. It also says students and educators can use Dify for free.
What can you build with Dify?
The homepage describes drag-and-drop creation of AI apps and workflows, access to multiple global LLMs, RAG pipelines, tools, agent strategies, observability, and MCP-based integrations. The pricing page also lists support for OpenAI, Anthropic, Llama2, Azure OpenAI, Hugging Face, and Replicate.
What integrations are documented on the site?
The source does not provide a complete integrations catalog, but it does mention native MCP integration, support for HTTP-based MCP services, and the ability to publish a workflow or agent as a standard MCP server.
Can Dify be used as a cloud service or self-hosted?
The education page indicates Dify Cloud Service for ready-to-use tools and Dify Community Edition for free self-hosted deployment on campus. The pricing page also distinguishes between cloud plans and self-hosted pricing.
Quick Facts
- Category
- Agentic workflow builder
- Platform
- Cloud service and self-hosted options
- Primary users
- Teams, developers, educators, and enterprise buyers
- Source domain
- dify.ai
- Notable workflow
- Drag-and-drop creation of AI apps, RAG pipelines, tools, and agents
- Pricing signal
- Free Sandbox plus paid plans; enterprise by contact sales
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