FlowiseAI/Flowise

Build AI Agents, Visually

What it solves

Flowise provides a visual interface for building AI agents, removing the need to write extensive code to orchestrate complex AI workflows.

How it works

It uses a drag-and-drop visual builder (React frontend) supported by a Node.js backend. The system allows users to integrate various third-party components and nodes to construct agentic workflows visually.

Who it’s for

Developers and AI practitioners who want to rapidly prototype and deploy AI agents without manually coding every integration.

Highlights

  • Visual builder for AI agents
  • Support for self-hosting via Docker or various cloud providers (AWS, Azure, GCP, etc.)
  • Mono-repository architecture consisting of a server, UI, and component library
  • Auto-generated Swagger-UI API documentation

Related

  • Project
    bytedance/flowgram.ai

    FlowGram is an open‑source visual workflow framework (bytedance/flowgram.ai) for building AI‑agent pipelines. It offers a web SDK and a native desktop app with drag‑and‑drop canvases, built‑in LLM, HTTP, and code nodes, scoped variables, form generation, debugging, and versioned publishing. Quick start via `npx @flowgram.ai/create-app@latest` and extensive docs at flowgram.ai.

  • Project
    coze-dev/coze-studio

    Coze Studio is an open-source, low-code visual development platform for creating, debugging, and deploying AI agents, workflows, and AI apps.

  • Project
    chatfire-AI/huobao-canvas

    An open-source, node-based canvas that lets users chain text, image, and video AI models from 11 providers into automated, visual creation workflows.

  • Project
    vercel-labs/workflow-builder-template

    A template for building AI-driven workflow automation platforms, featuring a visual drag-and-drop builder that generates executable TypeScript code.

  • Project
    writer/writer-framework

    An open-source framework for building AI applications that combines a visual drag-and-drop UI editor with a Python-based backend.