Hiveflow
Visual workflow orchestration for AI agents and automation
Flowise
Build and deploy AI agents visually with low-code workflows
Flowise is a visual builder for creating AI agents and LLM workflows using a drag-and-drop interface. Deploy chatbots, RAG pipelines, and multi-agent systems without extensive coding.
Overview
Visual AI Agent Builder
Flowise empowers developers and technical teams to design, prototype, and deploy AI agents through an intuitive visual interface. Built on LangChain, it bridges the gap between complex LLM orchestration and accessible low-code development.
Capabilities & Architecture
The platform supports chatbot creation, retrieval-augmented generation (RAG) pipelines, agentic workflows, and multi-agent systems. Its modular architecture includes a Node.js backend, React frontend, and extensible third-party integrations. Teams can chain together LLM providers, vector databases, tools, and custom logic nodes to build sophisticated AI applications.
Deployment Flexibility
Flowise runs locally via npm or Docker, and scales to production through self-hosted deployments on AWS, Azure, GCP, Digital Ocean, and other cloud platforms. The managed Flowise Cloud option provides instant hosting. With Apache License 2.0, teams retain full control over their implementations while benefiting from an active open-source community of contributors.
Highlights
Drag-and-drop visual editor for building LLM chains and agent workflows
Pre-built integrations with major LLM providers, vector stores, and tools
Self-hostable on any infrastructure or use managed Flowise Cloud
Extensible component system for custom nodes and third-party integrations
Pros
- Significantly reduces development time for AI agent prototyping
- Active community with 44K+ GitHub stars and regular contributions
- Flexible deployment options from local Docker to enterprise cloud
- Apache 2.0 license allows commercial use and modification
Considerations
- Visual abstraction may limit fine-grained control for complex use cases
- Requires Node.js 18.15+ and familiarity with npm/Docker tooling
- Low-code approach trades flexibility for convenience in some scenarios
- Documentation assumes baseline understanding of LLM concepts
Managed products teams compare with
When teams consider Flowise, these hosted platforms usually appear on the same shortlist.
Looking for a hosted option? These are the services engineering teams benchmark against before choosing open source.
Fit guide
Great for
- Rapid prototyping of chatbots and conversational AI applications
- Teams building RAG systems without deep LangChain expertise
- Organizations requiring self-hosted AI infrastructure for compliance
- Developers exploring multi-agent architectures and agentic workflows
Not ideal when
- Projects requiring highly custom LLM orchestration logic beyond visual nodes
- Non-technical users without access to developer setup or deployment resources
- Use cases demanding real-time performance optimization at scale
- Teams seeking fully managed AI platforms with zero infrastructure overhead
How teams use it
Customer Support Chatbot
Deploy a RAG-powered support bot that answers questions from your knowledge base with minimal coding
Document Analysis Pipeline
Chain together document loaders, embeddings, and LLMs to extract insights from unstructured data
Multi-Agent Research Assistant
Orchestrate specialized agents for web search, summarization, and fact-checking in a single workflow
Internal Tool Integration
Connect LLMs to company databases and APIs through visual nodes for custom enterprise automation
Tech snapshot
TypeScript54%
JavaScript33%
HTML7%
Handlebars6%
CSS1%
SCSS1%
Frequently asked questions
What are the system requirements to run Flowise?
Flowise requires Node.js version 18.15.0 or higher. You can run it locally via npm, or use Docker/Docker Compose for containerized deployment.
Can I self-host Flowise on my own infrastructure?
Yes, Flowise supports self-hosting on AWS, Azure, GCP, Digital Ocean, Alibaba Cloud, Railway, Render, and other platforms. Full deployment guides are available in the documentation.
What is the difference between self-hosting and Flowise Cloud?
Self-hosting gives you full control over infrastructure and data, while Flowise Cloud provides managed hosting with instant setup. Choose based on your compliance, customization, and operational needs.
How extensible is Flowise for custom integrations?
Flowise includes a components module for third-party integrations. Developers can create custom nodes and extend functionality through the mono-repository architecture.
Is Flowise suitable for production deployments?
Yes, Flowise is production-ready and supports environment variable configuration, API documentation, and deployment across major cloud providers with Docker support.
Project at a glance
Active- Stars
- 48,427
- Watchers
- 48,427
- Forks
- 23,628
Repo age2 years old
Last commit4 hours ago
Self-hostingSupported
Primary languageTypeScript
Last synced 48 minutes ago