Flowise

Flowise is an open-source visual builder for LLM applications that uses a drag-and-drop node interface to wire together language models, vector stores, retrievers, memory modules, and external tools into complete AI pipelines without requiring code for the configuration layer. Built on top of LangChain's primitives, Flowise exposes chains, agents, RAG pipelines, and tool-using systems as configurable visual flows, making LLM application architecture understandable and modifiable by team members without deep framework expertise. Teams use it to build: customer support chatbots trained on company documentation, internal research assistants grounded in organizational knowledge bases, multi-step research agents that combine web search with document retrieval, and API-integrated workflows that connect LLM processing with business system actions. The node library covers all major LLM providers, vector database integrations, document loaders, text splitters, memory types, and tool connectors, providing components for complete application construction.

Self-hosted deployment requires Docker and a supported database; the setup process is well-documented and straightforward for teams comfortable with containers. Flowise Cloud provides a managed version for teams without infrastructure management resources. The embedded chat widget deploys finished applications as a chatbot on any website. With over 38,000 GitHub stars, Flowise is among the most-used open-source LLM builders, particularly for teams who want LangChain's capabilities through a visual interface rather than code.