What is Flowise?
Flowise is an open source agent builder platform that lets teams design and deploy AI agents through a visual drag-and-drop interface. It covers single-agent chatbots and full multi-agent systems with LLM orchestration. The platform handles everything from conversational workflows to retrieval-augmented generation (RAG) pipelines pulling from multiple document types. Flowise runs on cloud or on-premises infrastructure and connects to 100+ LLMs, embedding models, and vector databases. It is available via npm install for self-hosting or through a hosted cloud account.
Flowise Video
Features & Benefits
- Multi-Agent Systems: Build coordinated multi-agent workflows using the Agentflow interface. Distribute tasks across multiple agents operating within a single orchestrated system.
- Chat Assistant Builder: Build single-agent chatbots with tool calling and knowledge retrieval (RAG) from documents including TXT, PDF, DOC, HTML, CSV, JSON, SQL, and more.
- Human-in-the-Loop (HITL): Route agent tasks to a human reviewer within the feedback loop before the agent proceeds. Keep oversight built into agentic workflows.
- Execution Traces and Observability: View full execution traces for every agent run. Connect to Prometheus, OpenTelemetry, and other observability tools to monitor performance.
- Embedded Chat Widget: Embed a chat interface directly into any web application. Configure and brand the widget to match the host product.
- Integrations: Connect to external services and data sources through a broad ecosystem of supported connectors including LLMs, vector databases, and embedding providers.
- Horizontal Scaling: Scale agent workloads using message queues and workers. Supports both cloud and on-premises deployment for production environments.
- Open Source Codebase: Access and modify the full source on GitHub. Self-host with a single npm command.
What can Flowise do?
- Build a multi-agent AI system visually
- Create a chatbot with document retrieval
- Deploy an AI agent to production
- Set up human-in-the-loop AI review
- Build a RAG pipeline from PDFs
- Run LLM workflows without writing code
- Connect an AI agent to external tools
- Embed a chat widget into a website
- Monitor AI agent execution traces
- Self-host an LLM application
Real-World Applications
Product and engineering teams building AI-powered features into their software may find the agent builder approach in Flowise significantly cuts down on development time. A team adding a knowledge base chatbot to an analytics platform can connect document sources, configure retrieval, and ship an embedded chat widget without building the orchestration layer from scratch.
Operations teams that need a human checkpoint in automated workflows can take advantage of the human-in-the-loop feature. Any agent handling sensitive decisions can pause and surface the task to a reviewer before it continues. This kind of agent builder setup keeps oversight in place without requiring a separate tool.
Businesses running AI at scale can deploy Flowise in on-premises environments and scale horizontally using message queues and workers. A company with strict data residency requirements can run the full agent builder stack inside its own infrastructure while still connecting to over 100 LLMs and vector databases.
Independent developers prototyping LLM applications can get a project off the ground quickly. Starting from a drag-and-drop canvas, they can wire together a complete agent flow, test it visually, and export it for production. The open source foundation means the underlying code is accessible and modifiable at every stage.
