Snapshot
Continue to About ↓- What it does
- Dify is a platform for building AI apps, agents, and retrieval-augmented (RAG) workflows on a visual canvas.
More detail
- Teams prepare knowledge bases, wire in models and tools from a marketplace, then publish as a web app, API, embed, or MCP tool and monitor usage.
- It runs as hosted Dify Cloud, self-hosted Dify Enterprise in a VPC, or the open-source Community Edition.
- Best for
- Developers and teams who want to build and ship agentic workflows and RAG apps on one collaborative, visual workspace.
More detail
- Enterprises with procurement, security, or audit needs that require self-hosting, SSO/SAML, RBAC, and audit logs.
- Pricing
- Dify Cloud is billed per workspace.
More detail
- The Professional plan is $590 per workspace per year (or monthly), including 5,000 message credits per month, 1 team workspace, 3 team members, 50 apps, 500 knowledge documents, 5GB knowledge storage, and 20,000 trigger events per month.
- The Team plan is $1,590 pe
- Main limitation
- Teams that want a fully managed, zero-configuration tool may find the Community Edition's Docker self-hosting a poor fit.
More detail
- Organizations with strict plain-Apache licensing requirements should review the 'Apache-2.0-derivative' license before adopting.
- Record
- Living and monitored
- Reviewed
- Evidence
- Public web research
- Machine access
- Structured profile ↗
About
- Dify is a platform for building AI apps, agents, and retrieval-augmented (RAG) workflows on a visual canvas.
- Teams prepare knowledge bases, wire in models and tools from a marketplace, then publish as a web app, API, embed, or MCP tool and monitor usage.
- It runs as hosted Dify Cloud, self-hosted Dify Enterprise in a VPC, or the open-source Community Edition.
What it helps with
- Prompt logic becomes invisible and hard to maintain across a team.
- AI stacks sprawl across separate model, tool, and data integrations.
- Unstructured documents are hard to ground AI answers in without a repeatable ingestion and retrieval pipeline.
- Prototypes require rework before they can run in production.
- Sensitive or high-stakes steps in a workflow need human review before continuing.
Capabilities
A practical view of what is available and where limitations apply.
| Offering | Available | Detail |
|---|---|---|
| Workflow Studio | Yes | Visual canvas with nodes for LLM calls, knowledge retrieval, question classification, branching, iteration, tools, code, and human input. |
| Agents | Yes | Build an agent by chatting or manual configuration; usable as an app, website embed, or an agent node inside a workflow. |
| Knowledge Pipeline (RAG) | Yes | Ingest files, websites, online documents, and drives; extract, clean, chunk, index, and test retrieval before connecting to agents or workflows. |
| Model and tool marketplace | Yes | Install model providers, tools, data sources, and MCP integrations; approved plugins can be reused across apps. |
| Publishing options | Yes | Publish apps as hosted experiences, API endpoints, embeds, or MCP-compatible tools. |
| Observability | Yes | Logs, feedback, annotations, latency, and usage data to understand and improve app behavior. |
| Enterprise security controls | Yes | Dify Enterprise lists SSO/SAML, RBAC, and audit logs, with SOC 2 Type II and ISO 27001 claims from the vendor. |
| Free tier | Limited | A free Sandbox plan is mentioned in the documentation, but its limits are not detailed in the provided evidence. |
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Evidence
Where this record came from, when it was reviewed, and how confidently it can be used.
- Verification
- Scribble researched these facts from the linked public sources.
- The owner has not manually confirmed every field.
- Last reviewed
- Primary source
- dify.ai
Technical profile details
Record ID
9be40643-abe3-4778-bde0-f9c7e11e4a8dCanonical URLhttps://profiles.scribble.network/listing/dify-9be40643