We package Flowise as an AWS AMI, so weigh that against everything below. Flowise vs Langflow is close, both are focused visual LLM builders with the same unconditional MIT license. n8n changes the comparison in two ways at once: it's a broader workflow automation platform where AI is one node among hundreds of integrations, and it isn't licensed the same way as the other two, a detail most roundups skip entirely.
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How to choose between them
Three questions cover most of it:
- Is the AI workflow the whole product, or one step in a bigger process? If it's the whole product, Flowise or Langflow fit better. If AI is one node inside a process that also touches your CRM, spreadsheets, and email, n8n's 400+ integrations do more of the surrounding work for you.
- Is your team JavaScript or Python? Flowise wraps LangChain.js, Langflow is native Python. Neither requires deep coding to use, but drop-to-code moments favor whichever language your team already knows.
- Are you planning to embed this commercially? If you're building a product on top of one of these and reselling it, or letting external users trigger workflows, check n8n's Sustainable Use License first, that specific use case needs a separate paid agreement, unlike Flowise or Langflow.
1. Flowise: drag-and-drop LangChain.js, unconditionally free
Flowise is MIT licensed with no restrictions on commercial use, built as a drag-and-drop wrapper around LangChain.js. It's designed to abstract away the code most people write by hand when building a RAG pipeline or chatbot, connect a document loader, an embedding model, and an LLM node on the canvas, and it handles the underlying orchestration. Flowise Cloud exists as a hosted option (Starter from $35/month, with a free tier of 2 flows and 100 predictions/month), but self-hosting costs nothing beyond your server.
Key features
- MIT licensed, no restriction on commercial or embedded use
- Drag-and-drop wrapper around LangChain.js, JavaScript/Node.js stack
- Fast path from a blank canvas to a working RAG chatbot
- Optional Flowise Cloud hosting, free tier plus paid tiers from $35/month
2. Langflow: Python-first, backed by IBM, still fully MIT
Langflow is 100% open source under the MIT license, giving the same unconditional commercial-use freedom as Flowise. It's built natively in Python, which suits data and ML teams who want to intervene in code when the visual canvas hits its limits, rather than staying purely drag-and-drop. DataStax acquired Langflow in 2025, and DataStax itself was acquired by IBM in a deal that closed May 28, 2025, so Langflow is now effectively IBM-backed while remaining fully open source under the same MIT terms. Managed hosting through third-party providers starts around $16/month if you'd rather not self-host.
Key features
- MIT licensed, unconditional commercial and embedded use allowed
- Native Python, built for teams that want to drop into code from the canvas
- Now backed by IBM via the DataStax acquisition, still open source
- Third-party managed hosting available from roughly $16/month
3. n8n: the automation platform AI got added to
n8n is best described as self-hostable Zapier with LangChain-based AI agent nodes added on top, over 400 integrations covering CRMs, spreadsheets, email, and most SaaS tools a business already runs. That breadth is the actual pitch: AI is one node type among many, useful when the workflow needs to touch several other systems, not just call an LLM. The catch is licensing: n8n's core ships under a Sustainable Use License, fair-code rather than fully open source, free for internal business use and non-commercial purposes, but embedding n8n in a product you sell, reselling automation as a service, or letting external users trigger workflows all require a separate commercial agreement and fees. n8n Cloud starts around 24 euros a month if you'd rather not self-host.
Key features
- 400+ integrations across CRMs, spreadsheets, email, and general SaaS tools
- LangChain-based AI agent nodes alongside traditional automation nodes
- Sustainable Use License: free for internal/non-commercial use, paid agreement required for embedding or reselling
- n8n Cloud hosting available from roughly 24 EUR/month
The licensing catch most roundups skip
Flowise vs n8n and Langflow vs n8n both hinge on this more than most comparisons admit. Flowise and Langflow are MIT licensed, full stop, no condition attached to how commercial your use case is. n8n's core is licensed under a Sustainable Use License: you can self-host and run it internally for free, and non-commercial redistribution is fine, but the moment you embed n8n inside a SaaS product, resell automation built on it as a service, or let external users trigger its workflows, you need a signed commercial agreement with n8n and owe them fees. That's not a criticism of n8n's model, fair-code licensing is a legitimate way to fund an open project, but calling all three of these tools equally "open source" without that distinction misleads anyone planning a commercial product on top of one.
Flowise vs Langflow vs n8n: feature comparison
| Feature | Flowise | Langflow | n8n |
|---|---|---|---|
| License | MIT | MIT | Sustainable Use License |
| Free for commercial embedding | Yes | Yes | No, requires paid agreement |
| Language / stack | JavaScript/Node.js, LangChain.js | Python | Node.js, general automation engine |
| Primary focus | RAG pipelines, chatbots, agents | LLM chains and agents, code-friendly | General workflow automation, AI as one node type |
| Integration count | Focused on LLM/vector store connectors | Focused on LLM/vector store connectors | 400+ across CRMs, SaaS, spreadsheets |
| Cloud hosting | Flowise Cloud from $35/month | Third-party from ~$16/month | n8n Cloud from ~24 EUR/month |
| Backing | Independent open source project | IBM (via DataStax acquisition) | n8n GmbH |
Why we run Flowise for clients
Most teams that come to us wanting a visual AI builder are trying to ship a RAG chatbot or agent quickly, not automate their whole back office, which puts them squarely in Flowise or Langflow territory rather than n8n's. We picked Flowise specifically because it's JavaScript-native, which matches the stack most of our clients' engineering teams already run, and because MIT licensing means nobody has to check a commercial-use clause before shipping. We package it as a ready-to-launch AMI so the setup, Node.js, the vector store, environment variables for whichever LLM provider you're using, is done before the instance finishes booting.
Our Flowise developer guide and Flowise AWS Marketplace guide cover the setup in full. If you're pairing Flowise with a self-hosted model instead of a hosted API, our OpenWebUI with Ollama guide and Mistral developer guide cover running the model side yourself.
Where I'd start
Building a RAG chatbot or agent as the product itself, and your team is JavaScript: Flowise. Same goal, but your team is Python and wants to drop into code: Langflow. Automating a broader business process where AI is one step among many, and you're not embedding it commercially: n8n, its 400+ integrations do real work the other two don't attempt.
If commercial embedding or reselling is part of the plan, read n8n's Sustainable Use License terms before building on it, that's the one decision here that isn't reversible after the fact.
Frequently Asked Questions
Flowise vs Langflow: which should I pick?
Flowise if your team is JavaScript/Node.js and wants the fastest drag-and-drop path to a working RAG chatbot. Langflow if your team is Python-native and wants to drop into code when the visual canvas isn't enough. Both are unconditionally MIT licensed, so licensing isn't the deciding factor between these two specifically.
Flowise vs n8n: what's the real difference?
Flowise is a focused LLM and agent builder, at its best building a RAG pipeline or chatbot fast. n8n is a general workflow automation platform (400+ integrations) where AI is one node type among many. n8n is also licensed under a Sustainable Use License, not unconditional MIT like Flowise, which matters if you're embedding it commercially.
Langflow vs n8n: which is better for building AI agents?
Langflow, if the agent itself is the product, its canvas is purpose-built for LLM chains and agent logic. n8n is stronger when the AI step is part of a larger business process that also touches CRMs, spreadsheets, and other systems across its 400+ integrations.
What is a genuinely open source ai agent builder open source option?
Flowise and Langflow both qualify unconditionally, MIT licensed with no restriction on commercial or embedded use. n8n's core is source-available under a Sustainable Use License, free for internal and non-commercial use, but commercial SaaS, reselling, or embedding requires a separate paid agreement with n8n.
Is n8n actually free for commercial use?
For running it internally to automate your own company's processes, yes. For embedding n8n inside a product you sell, reselling automation as a service, or letting external users trigger workflows, no, those uses require a signed commercial agreement and fees, per n8n's own Sustainable Use License terms.
What's a good visual llm builder for a non-Python team?
Flowise. It's built entirely in JavaScript and Node.js, wrapping LangChain.js, which fits naturally into a team already working in the JS ecosystem rather than requiring a Python runtime alongside everything else.
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