Enterprise DNA
O Open Source Orchestration medium

Flowise

by Community

Build AI Agents, Visually

F

OSS

Flowise

Added 1 June 2026

#agentic-ai #agentic-workflow #agents #artificial-intelligence #chatbot #chatgpt #javascript #langchain

Overview

Flowise is a visual orchestration platform for building AI agents and workflows without code. It provides a drag-and-drop interface to connect LLMs, data sources, and tools into executable agent pipelines. Built in TypeScript and open source, it runs self-hosted or cloud-deployed.

Best for

Best for
Teams building AI agents who want visual composition without writing orchestration code

Use cases

  • Prototyping multi-step AI workflows with LLM chains
  • Building chatbots that integrate external APIs and databases
  • Creating autonomous agents that reason and take actions

Notes

Flowise is a visual orchestration platform for building AI agents and workflows without code. It provides a drag-and-drop interface to connect LLMs, data sources, and tools into executable agent pipelines. Built in TypeScript and open source, it runs self-hosted or cloud-deployed.

53,254 stars on GitHub. Last updated 2026-05-30.

Use cases

  • Prototyping multi-step AI workflows with LLM chains
  • Building chatbots that integrate external APIs and databases
  • Creating autonomous agents that reason and take actions

Pros

  • Visual builder reduces friction for non-engineers to compose complex agent logic
  • Open source with large community (53k+ stars) and self-hosting option
  • Native support for multiple LLM providers and tool integrations

Cons

  • Visual paradigm can become unwieldy for highly complex or deeply nested workflows
  • Requires deployment and infrastructure management for production use
  • Community-driven project with no commercial support guarantee

Indexed from awesome-langchain and enriched against its public facts.

Pros

  • Visual builder reduces friction for non-engineers to compose complex agent logic
  • Open source with large community (53k+ stars) and self-hosting option
  • Native support for multiple LLM providers and tool integrations

Cons

  • Visual paradigm can become unwieldy for highly complex or deeply nested workflows
  • Requires deployment and infrastructure management for production use
  • Community-driven project with no commercial support guarantee

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