# Flowise

> Open-source, low-code visual builder for LLM apps and AI agents — drag-and-drop to assemble chains, agents, and RAG; self-host or use Flowise Cloud.

Flowise is an open-source, low-code platform for building LLM apps and AI agents on a drag-and-drop canvas. You wire nodes into chains, agents, and RAG flows, then self-host the Apache-2.0 core or run Flowise Cloud. Built flows expose an API and embed widget, so prototypes ship as real product surfaces.

Website: https://flowiseai.com

Flowise is a **low-code, visual builder for LLM apps and AI agents**. Instead of hand-writing orchestration, you drag nodes onto a canvas and connect them into chains, agentic systems, and retrieval-augmented (RAG) flows — its homepage positions it plainly as "Build AI Agents, Visually," an open-source agentic-systems development platform.

It targets developers and technically-minded builders who want to prototype and ship LLM features fast without wiring every model call, memory store, and tool by hand. Run it locally with one npm command, self-host the Apache-2.0 core on your own infrastructure, or use the managed Flowise Cloud. Because every flow is exposed as an API and an embeddable widget, Flowise fits an AI-assisted workflow as the visual layer between a model provider and a real product surface.

## Highlights

- **Drag-and-drop flow builder** — assemble logic visually on a canvas, inspect each node's input/output, and iterate without redeploying code.
- **Agents, RAG, and chains as nodes** — build multi-agent systems, retrieval pipelines over your documents, and tool-using chains from composable building blocks.
- **Self-hostable with an API** — own the deployment, then call any flow over its REST API or drop in the embed widget to put it in an app.
- **Large integration ecosystem** — connect many model providers, vector stores, document loaders, and tools, so flows reach real data and services.

## In an AI-assisted workflow

Flowise sits between your model provider and your product: build a flow visually, test it on the canvas, then call its endpoint from your app. Spin it up locally in seconds:

```bash
npx flowise start
# open http://localhost:3000
```

For where this slots against automation-first and app-first tools, see [n8n vs. Dify](/guides/comparisons/n8n-vs-dify).

> [!TIP]
> Prototype the flow in the visual editor, then promote it by calling its generated API from your codebase — the canvas stays the source of truth while your app just consumes the endpoint.

## Good to know

License matters here. The Community Edition is **Apache-2.0** — permissive enough to self-host, modify, and use commercially, including running it as a service. A separate Enterprise Edition ships inside the repo's `/enterprise` directory under a commercial license and stays inactive without a license key, so confirm which edition you're deploying before building a SaaS on it. Flowise Cloud is the paid managed path (a free tier plus paid plans starting around $35/month — verify current pricing on the official site). For how it stacks up against other visual builders, see [Best AI App Builders (2026)](/guides/comparisons/best-ai-app-builders-2026).
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_Source: https://agentscamp.com/tools/flowise — Tool on AgentsCamp._