Flowise

Flowise sits in the same space as Langflow and Dify: a visual canvas where you drag-and-drop components to build agent workflows without writing the orchestration code yourself. Each node in the canvas represents a step, such as loading a document, running a model, calling a tool, or applying a filter. You connect them with edges, set the configuration in a sidebar, and Flowise generates the underlying code and hosting for you.

It's built on LangChain (a popular agent and LLM orchestration library) under the hood, which means it inherits a large ecosystem of pre-built integrations: vector databases (storage systems for semantic search), memory backends, dozens of model providers, and tool connectors. The open-source version is self-hostable, and a hosted cloud version is available for teams that don't want to manage infrastructure. With over 51,000 GitHub stars and an active 2026 commit history, it's one of the three most-starred visual agent builders on GitHub alongside Langflow and Dify.

For builders who aren't comfortable writing raw agent orchestration code, Flowise is a fast way to prototype RAG pipelines (systems that retrieve relevant context before generating a response) or multi-step agent workflows. The tradeoff is the usual one for visual builders: easy to start, harder to customize deeply or debug when something goes wrong at the node level. Many teams use it for internal tools and proofs of concept, then migrate to code-first frameworks for production.