Flowise is an open-source, low-code platform for building AI agents and LLM workflows through an intuitive drag-and-drop visual interface, enabling developers to create chatbots, intelligent assistants, and complex AI pipelines without writing extensive code. It solves the challenge of making LLM application development accessible by providing visual builders where components like LLMs, prompts, tools, retrievers, memory, and control flow can be connected through a node-based editor. Flowise bridges the gap between no-code simplicity and developer flexibility, allowing rapid prototyping of AI applications that can be deployed as production APIs.
Flowise organizes its capabilities around three visual builders: Assistant for creating simple chat assistants, Chatflow for single-agent systems and basic LLM flows, and Agentflow for comprehensive multi-agent systems and complex workflow orchestration. The platform supports flexible document loaders, multiple embedding providers, various vector stores, and configurable retrievers for building RAG systems, along with integrations for LangChain, LlamaIndex, and other AI frameworks. Flowise is typically self-hosted via Docker and provides REST API endpoints for integrating built workflows into existing applications, with support for authentication, rate limiting, and conversation memory.
Flowise targets developers, AI enthusiasts, and business teams who want to build and deploy AI applications rapidly without deep expertise in LLM programming or infrastructure management. It integrates with major LLM providers including OpenAI, Anthropic, Google, and open-source models through Ollama, plus vector databases like Pinecone, Weaviate, and Chroma for RAG capabilities. Flowise is particularly popular among teams building internal tools, customer support chatbots, and document Q&A systems, where the visual development approach allows for rapid iteration and easy modification of AI workflows without requiring code changes.
