Open-source LLM app and agent platform with a visual workflow canvas, RAG pipelines, and one-click cloud or self-hosted deployment.

Overview

Dify is an open-source platform for building, testing, and operating LLM-powered applications - chatbots, text generators, retrieval-augmented assistants, autonomous agents, and multi-step workflows - without writing an orchestration layer from scratch. Built by LangGenius, it bundles what would otherwise be several tools: a drag-and-drop workflow canvas, a prompt IDE, a knowledge-base pipeline for RAG, an agent framework with tool use, model management across hundreds of LLMs, and observability for logs, cost, and quality. Every app is exposed via API, so Dify can act as a backend-as-a-service for your own products. The same core runs as a free self-hosted Community Edition or as a managed cloud service, which is often the deciding factor for teams that need data to stay inside their own perimeter.

Key Features

  • Visual Workflow Studio: turn prompt logic into a visible, debuggable execution path
  • Agents with tools, memory, and boundaries, usable standalone or as workflow nodes
  • Knowledge pipelines that extract, chunk, index, and test retrieval before going live
  • Plugin Marketplace for model providers, tools, data sources, and MCP integrations
  • Publish as web app, API, embed, or MCP-compatible tool with logs and feedback
  • Self-host with one Docker command or run managed Dify Cloud with SSO and RBAC

Pricing

PlanPriceFor
Community (Self-hosted)$0Docker deploy, full features, unlimited apps
Sandbox$0Try core features, 200 message credits
Professional$59/moIndie devs and small teams in production
Team$159/moMid-size teams, unlimited apps and members
EnterpriseCustomSSO, compliance, SLA, dedicated support

Comparison

Compared to Coze, Dify targets builders who need to self-host and own their stack, while Coze leans toward quick consumer bots. Against CrewAI, Dify gives a visual canvas instead of writing multi-agent orchestration in Python. Versus Manus, Dify is a platform you deploy and operate yourself rather than a hosted agent you simply prompt.

Hands-on Verdict

Dify is the LLM-app platform I use to build agents and RAG pipelines with a visual backend — datasets, prompts, and tools wired together, then shipped as an API. It’s more backend-complete than Flowise on ops and more flexible than Chatbase. For no-code browser agents I use Agent.ai.

Who it’s for: developers, product teams. Tip: load and chunk your knowledge base carefully before prompting — Dify’s RAG quality lives or dies on the dataset, so clean sources first.

Compare alternatives

Side-by-side with the 3 closest alternatives.

ToolCategoryPricingVisit
Dify (this) agents, productivityFrom $0/mo Site ↗
CozeagentsFree $0/mo · From $9/mo Site ↗
CrewAIagents, codeFrom $0/mo Site ↗
ManusagentsCustom pricing Site ↗
Dify Current

Open-source LLM app and agent platform with a visual workflow canvas, RAG pipelines, and one-click cloud or self-hosted deployment.

agentsproductivity
From $0/mo

ByteDance's free low-code platform for building, deploying, and publishing AI chatbots and agents across Discord, Telegram, Slack, and the web.

agents
Free $0/mo · From $9/mo

Open-source framework to orchestrate teams of collaborating AI agents. Multi-agent orchestration Read our hands-on review and compare the top AI Agents

agentscode
From $0/mo

General-purpose autonomous AI agent that plans, browses the web, and completes multi-step tasks in the cloud. Genuinely autonomous end-to-end task

agents
Custom pricing
Editor’s Review
4.5/5
Pros
  • +Free self-hosted Community Edition with the full feature set, no artificial gating
  • +Visual workflow canvas plus RAG, agents, prompt IDE, and LLMOps in one place
  • +Transparent cloud pricing from $59/workspace/mo, no per-seat surprises
Cons
  • Source-available license has conditions stricter than pure Apache
  • Cloud plan ceilings push growing teams toward custom enterprise quotes
  • Self-hosting carries the operational burden any DIY stack implies

Dify is the most complete open-source LLM app platform of 2026 - a small team can stand up chatbots, RAG, and agents in an afternoon. It is held back only by a restrictive 'open source' license, cloud ceilings that nudge you to sales, and the upkeep self-hosting always demands.

See all reviews →

Last updated: 2026-07-31

When to use it

  • Use it when you need free self-hosted Community Edition with the full feature set, no artificial gating
  • Use it when you need visual workflow canvas plus RAG, agents, prompt IDE, and LLMOps in one place
  • Use it when you need transparent cloud pricing from $59/workspace/mo, no per-seat surprises

When to skip it

  • Avoid it if source-available license has conditions stricter than pure Apache
  • Avoid it if cloud plan ceilings push growing teams toward custom enterprise quotes
  • Avoid it if self-hosting carries the operational burden any DIY stack implies

Alternatives to consider