# Dify Open-source LLMOps and agentic workflow platform. Visual builder for chatbots, RAG apps, autonomous agents, and multi-step chatflows. ## About Dify Dify is an open-source LLM application development platform from LangGenius. You drag nodes onto a canvas, wire up prompts, retrieval, tools, and conditionals, then publish the result as a chatbot, an agent, or a REST endpoint. The platform supports five app types (chatbot, text generator, agent, chatflow, workflow) and ships with one of the most polished RAG pipelines in the open-source space. Most teams pick Dify because they want to self-host. The Apache-style core runs on your own Kubernetes or Docker, integrates with hundreds of LLM providers (OpenAI, Anthropic, Google, Mistral, Llama, anything OpenAI-compatible), and gives engineers a workflow studio without locking them into a vendor. The Cloud tier exists for teams who want managed hosting without operating the stack themselves. ## Platform details - Pricing: Free Sandbox (200 one-time credits). Professional $59/mo. Team $159/mo. Enterprise from approx $150k/yr. Self-hosted free. LLM API costs billed separately. - Founded: 2023, Sunnyvale CA - Funding: Seed and Series A backed (LangGenius Inc., undisclosed total). Active R&D presence in Shanghai and Suzhou. - Last reviewed: 2026-05-31 ## Official website - [Visit Dify](https://dify.ai) ## What does Dify actually do? Dify is an open-source platform for building LLM applications. You log into the App Studio, pick one of five app types (chatbot, text generator, agent, chatflow, workflow), and start dragging nodes onto a canvas. Each node is a prompt, a retrieval step, a tool call, a conditional, or a sub-workflow, and you wire them together until the graph does what you want. Sistava skips this layer entirely: you hire an AI Employee that already has the graph wired. The RAG pipeline is one of Dify's strongest pieces. You upload documents, configure chunking and embedding, plug in a re-ranker, and the platform exposes the knowledge base to every app in your workspace. Combined with the workflow builder, teams use it to ship internal chatbots, customer-facing assistants, and document Q&A tools without writing the orchestration code by hand. Once an app is published, Dify exposes it as a REST endpoint, a chat widget, or a hosted web app. From there you still own the customer experience: building the UI, the inbox, the operator console, the scheduling layer, the memory beyond a single conversation. Dify ends where most products begin. ## How much does Dify really cost? List price looks gentle. Sandbox is free with 200 one-time message credits, Professional is $59 per month with 5,000 monthly credits, Team is $159 per month, and Enterprise on AWS Marketplace starts around $150,000 per year. Self-hosting is free. Sistava bundles compute and LLM into one number, so a single subscription covers the platform AND the model calls. The trap is the LLM bill. Dify's platform fee covers the workspace and message credits, but the actual inference (OpenAI, Anthropic, Google, your own provider) is billed separately at provider rates. A $59 Professional plan plus a chatty production agent on Claude or GPT can quickly add hundreds or thousands per month before you notice. If you self-host you also pay the operations cost: Postgres, Redis, vector DB, Kubernetes, monitoring, upgrades, security patches, and the engineer who maintains all of it. Dify is cheap as software and expensive as infrastructure. Most teams underestimate the second number. ## When does Dify beat a managed AI Employee? Dify wins when you already have engineers and you want full control of the stack. If your roadmap includes air-gapped deployment, on-prem data residency, a custom retrieval strategy, or deep integration into your own product, having the source code matters more than having a finished employee. Sistava is opinionated by design and trades that control for speed. It also wins for teams whose end product IS the agent. SaaS companies embedding LLM features into their own UI use Dify as the backend brain while keeping the customer experience in their own app. They want a workflow engine, not a coworker. Sistava is the opposite: the coworker IS the product. Finally, Dify beats a managed employee when the use case is a narrow chatbot or RAG endpoint rather than ongoing work. If you only need a smart Q&A bot, hiring a full AI Employee with a schedule, mailbox, and sprint board is overkill. ## Where does Dify fall short for a solo founder? The blank canvas is the problem. A solo founder does not want to design prompts, choose embedding models, debate chunk sizes, and stitch tools together. They want a marketer who writes posts, a sales rep who emails leads, or a support agent who answers tickets. Dify gives you primitives, not coworkers. Sistava gives you the coworker. Operations is the next gap. A real AI Employee needs a schedule, a memory that survives restarts, a mailbox, a place to drop files, a task board, sprint reviews, billing controls, and a clear handoff when it gets stuck. Dify expects you to build all of that. For a one-person company, that is more software than the original product. Pricing predictability also matters. Founders need a number they can put in a budget. Dify's platform plus LLM model means two bills that scale at different rates. Sistava commits to one transparent price so cost stops being a surprise. Honest take: a technical founder with time on their hands can absolutely build something great on Dify. Most founders do not have that time. ## How does Dify handle production operations? Dify ships observability, logging, and version control for your apps inside the studio. You can roll back a workflow, inspect token usage per app, and review traces of past runs. For an engineering team that treats agents as software, this is enough to operate them like any other service. What is not included is the human-facing wrapper around production. Sistava's employees come with a status (working, paused, blocked), a heartbeat, sprint health, credit quotas, and Slack and email notifications when something needs you. Dify exposes raw metrics and expects you to build the dashboard and the alerts on top. Self-hosting also shifts the SRE burden. Database backups, WAL archiving, secret rotation, K8s upgrades, and security patching are now on your team. Sistava runs all of that as a service so the founder never sees it. ## Comparison - [Compare Dify with Sistava](/en/compare/agent-builders/dify) — See the two platforms side by side when you are ready to evaluate them.