Build AI chatbots, RAG pipelines and agents by connecting nodes on a canvas. Flowise runs from a pre-configured AMI in your own AWS account, so your flows, API keys and conversation logs stay with you.
Flowise is an MIT-licensed, low-code platform for building LLM applications with a visual drag-and-drop interface built on LangChain.js. You wire together a model, a data source, memory and an output, and Flowise handles the orchestration.
Build chatbots, RAG pipelines and agents without application code.
OpenAI, Anthropic, Hugging Face, Cohere, Vertex AI, Azure OpenAI and Ollama.
Each flow gets an endpoint you can call from any front end.
Drop a chatbot into your website without building a UI.
Clone official templates for chatbots, RAG and multi-agent flows.
Extend a flow with code when drag-and-drop is not enough.
The AMI ships Flowise ready to use, with login and SSL handled at launch.
Subscribe on AWS Marketplace and launch the CloudFormation stack with your domain and Flowise login.
After 5-10 minutes, create a DNS record for your domain with the PublicIp from the stack outputs.
Open the DashboardUrl and log in with the Flowise username and password you set.
Add your LLM API key, start from a template, and embed the chatbot or call its API.
An AMI on AWS Marketplace, launched into your own AWS account with CloudFormation or from EC2.
Launch on AWS The vendor-recommended security group opens these ports.
| Service | Ports | Protocol |
|---|---|---|
| HTTP and HTTPS | 80, 443 | TCP |
| SSH (administration) | 22 | TCP |
| Flowise | Langflow | n8n | |
|---|---|---|---|
| Licence | MIT | MIT | Sustainable Use License |
| Free for commercial embedding | Yes | Yes | No, needs a paid agreement |
| Stack | Node.js, LangChain.js | Python | Node.js automation engine |
| Focus | RAG pipelines, chatbots, agents | LLM chains and agents | General workflow automation |
Pick by team language and by how you plan to use the tool commercially. Read Flowise vs Langflow vs n8n →
Building LLM applications visually: AI chatbots, document Q&A, RAG pipelines and autonomous agents, by connecting nodes on a canvas.
LangChain is a library you use in code. Flowise is a visual interface built on LangChain concepts, which makes prototyping a chatbot or RAG pipeline faster.
OpenAI, Anthropic, Hugging Face, Cohere, Google Vertex AI, Azure OpenAI, Ollama for local models, and others. You bring your own API keys.
Not for most use cases. Chatbots, RAG pipelines and basic agents are drag-and-drop; custom code nodes are there if you need them.
Yes. Every flow has an API endpoint, and Flowise includes an embeddable chat widget for websites.
t3a.medium is the recommended starting point on AWS.
Automatically if your domain is hosted on Route 53. Otherwise SSH in and run sudo /root/certificate_generate_standalone.sh.
Back up your flows and configuration, remove the old stack and launch the updated AMI from AWS Marketplace.
Stacks, focus and the licensing detail most roundups skip.
Build chatbots, RAG pipelines and agents on your own infrastructure.
Launch the stack, set up DNS and SSL, and sign in.
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