Flowise is a drag-and-drop open-source platform for building LLM agents, chatbots and retrieval workflows, popular for how quickly a working assistant can come together.
Flowise chains models, memory, tools and vector databases on a visual canvas, with a large library of templates covering customer support, document QA, sales agents and more. Its agent executors support tool use and multi-agent setups, and the whole platform runs locally with a single command.
Beyond prototyping, Flowise provides production features: embeddable chat widgets, API endpoints, credentials management, rate limiting, analytics and agent observability. It supports OpenAI, Anthropic, Google, Azure, AWS Bedrock and local models, and can integrate with LangChain and LlamaIndex components for advanced retrieval. Templates cover common patterns such as document question answering, sales qualification and support triage, so time to first working demo is often under an hour. Community sharing of flows keeps the ecosystem growing quickly.
Flowise is open source and free to self-host. Hosted cloud plans start with a free tier and scale with flows, messages and team members, while enterprise plans add SSO, dedicated support and on-premise deployment assistance. Self-hosting is free and lightweight enough to run on modest hardware, while cloud plans scale gently with message volume and team size.
Flowise targets startups, agencies and internal teams that need working chatbots and agents fast, without hiring a full ML engineering group. It is also popular with consultants delivering client solutions on tight timelines. Consultants in particular value being able to deliver polished client demos quickly and then hand over a system clients can maintain themselves.
Yes, the open-source version is free with full functionality, and the cloud offers a free tier for small projects. Paid plans add capacity, collaboration and support.
Yes, every chatflow and agentflow can be called via API, and the platform provides embeddable widgets plus webhook triggers for event-driven automation.
Flowise is faster to start with than code frameworks and more agent-capable than classic chatbot builders. Dify offers deeper operations tooling, while Flowise wins on template breadth and ease for non-developers. Flowise wins when speed and simplicity matter most; teams with complex stateful logic usually migrate toward code-first frameworks once their needs outgrow the canvas.