Flowise is an open source, low code tool for building LLM applications through a visual drag and drop interface. Users assemble chatflows and agents by connecting nodes that represent models, prompts, memory, data sources, and tools. It draws on popular language model libraries so builders can create retrieval pipelines, chatbots, and autonomous agents without writing much code. Flowise can be self hosted or run through its cloud service, and finished flows are exposed as APIs or embeddable chat widgets for integration into other products and sites.
The tool is aimed at developers, technical builders, and teams that want to prototype and ship LLM features visually while keeping the flexibility of open source. It suits people building customer support bots, internal knowledge assistants, and experimental agent workflows. Because it abstracts away boilerplate, less experienced developers can still produce working applications, while advanced users extend flows with custom code and integrations. Organizations that want data control often self host it rather than relying on a closed platform for these workloads.
In practice, builders drag nodes onto a canvas, wire them into a flow, and test responses directly in the interface. Flows connect to vector stores, APIs, and multiple models. Once ready, they are deployed as endpoints or embedded widgets for use in applications.
