Flowise AI
by FlowiseAI
Flowise is an open-source, low-code visual builder for creating LLM applications and agents by dragging and connecting nodes representing models, prompts, tools, and data sources. It generates working LLM pipelines — including RAG chatbots…
Definition
Flowise is an open-source, low-code visual builder for creating LLM applications and agents by dragging and connecting nodes representing models, prompts, tools, and data sources. It generates working LLM pipelines — including RAG chatbots and multi-step agents — without requiring developers to write orchestration code by hand.
Overview
Flowise (often called FlowiseAI) provides a node-based visual editor, conceptually similar to tools like n8n or Node-RED, but specialized for building applications powered by large language models. Users construct a flow by dragging nodes onto a canvas — for example, a document loader, a text splitter, an embedding model, a vector store, and a chat model — and connecting them to define how data moves through the pipeline, without writing the underlying integration code. Under the hood, Flowise builds on concepts popularized by frameworks like LangChain and LlamaIndex, exposing many of the same building blocks (chains, agents, tools, memory, retrievers) as visual components. This makes it accessible to developers who want to prototype quickly or to less code-heavy teams who need to assemble an LLM workflow without deep framework knowledge. Completed flows can be deployed as a chat widget, exposed via a REST API, or embedded into other applications, and Flowise also supports agentic flows where an LLM can choose among multiple tools (web search, calculators, custom APIs) to complete a task. Flowise is self-hostable via Docker or npm and also offers a hosted cloud version. It supports a wide range of LLM providers (OpenAI, Anthropic, local models via Ollama, and others) and vector stores, making it provider-agnostic. It competes directly with similar visual LLM-orchestration tools such as Langflow and n8n's AI nodes, differentiating through its close alignment with LangChain's component model and its focus on rapid, code-optional prototyping of chatbots and agents that can still be exported to code or embedded via API for production use.
Key Features
- Drag-and-drop visual builder for LLM chains and agents
- Node library mirroring LangChain/LlamaIndex concepts (chains, agents, retrievers, memory, tools)
- Supports multiple LLM providers including OpenAI, Anthropic, and local models via Ollama
- Built-in support for RAG pipelines with document loaders, splitters, and vector stores
- Deployable flows as embeddable chat widgets or REST API endpoints
- Agentic flows enabling tool selection and multi-step reasoning
- Self-hostable via Docker/npm, with an optional hosted cloud offering
- Open-source with an active plugin/node ecosystem
Use Cases
Alternatives
History
Flowise is an open-source, low-code platform for building LLM applications and AI agents through a drag-and-drop visual interface, built on top of frameworks like LangChain. It was founded in 2023 by Henry Heng and Chung Yau Ong, who had been assembling LLM apps with open-source frameworks and wanted a faster, more visual way to prototype without repetitive boilerplate; the project went through Y Combinator. Released as open source (Apache 2.0), Flowise lets both technical and non-technical users compose chatbots, RAG pipelines, and agentic workflows and deploy them, with ready-made templates. It became one of the most widely used visual builders for generative-AI applications.
Sources
- Flowise — official website · as of 2026-07-17
- Flowise on GitHub — FlowiseAI/Flowise · as of 2026-07-17