Flowise vs Stack AI
Updated March 10, 2026
Overview
Flowise is an open-source drag-and-drop UI for building LLM flows and AI agents. Built on top of LangChain, it lets users visually connect LLMs, prompts, tools, memory, and vector stores into working applications without writing code. Flowise can be self-hosted and is popular with teams that want the power of LangChain with a visual interface.
Stack AI is a no-code platform for building AI workflows and applications. It provides a visual drag-and-drop interface for creating RAG pipelines, chatbots, document processing workflows, and AI agents. Stack AI connects to enterprise data sources and deploys as APIs or embeddable widgets.
Key features
Core capabilities each platform advertises.
- Open-source visual LLM workflow builder
- Drag-and-drop node interface
- LangChain integration
- Custom components
- Self-hosted deployment
Strengths and tradeoffs
What each tool does well, and the limitations to keep in mind.
Pros
- Low-code
- Open-source
Cons
- Limited control
Pros
- Production-ready
- Good performance
- Active development
Cons
- Pricing varies
- Setup required
Flowise or Stack AI — which should you choose?
Choose Flowise if you wantChoose if you want
- Visual RAG pipeline building
- LLM workflow prototyping
- Custom AI tool creation
- AI application experimentation
- No-code LLM chain building
Choose Stack AI if you wantChoose if you want
Compare Flowise and Stack AI on your own traffic
Respan lets you trace LLM and agent calls across any model or framework, A/B test prompts on production traffic, and route requests across 500+ models through one gateway.