n8n vs LangChain
Side-by-side comparison to help you choose the right tool for your business
Our Verdict: n8n for business automation, LangChain for custom AI agent development
These solve fundamentally different problems, but they keep showing up in the same buying conversation. n8n is a visual workflow builder that happens to have excellent AI nodes — you drag, drop, connect, and deploy. LangChain is a developer framework for building custom AI agents from scratch. If your team has a Python developer and needs agents that do things no off-the-shelf tool can do, LangChain is the answer. If your team needs to connect AI to their existing tools and get results this week, n8n is the answer. We've seen teams waste months building in LangChain what n8n could have done in an afternoon.
At a Glance
n8n
Business teams automating workflows with AI capabilities
Free (self-hosted) / $20+/mo (Cloud) / Custom (Enterprise)
intermediate
1-5 days
LangChain
Developers building custom AI agents and RAG pipelines
Free (open source) / LangSmith from $39/mo
advanced
2-8 weeks
Feature Comparison
| Feature | n8n | LangChain |
|---|---|---|
| Visual builder | Yes (drag-and-drop) | No (code only) |
| Coding required | Optional (for custom nodes) | Required |
| Pre-built integrations | 400+ connectors | 200+ LLM/tool integrations |
| Custom agent logic | Limited to node combinations | Unlimited (code) |
| RAG pipelines | Yes (via AI nodes) | Yes (core feature) |
| Multi-agent orchestration | Basic | LangGraph (advanced) |
| Production monitoring | Execution logs | LangSmith (full tracing) |
| Self-hosting | Yes | Yes (open source) |
Which to Choose by Use Case
Connecting ChatGPT to your CRM and email
Pre-built connectors mean you can set this up in an hour, not a sprint
Building a custom RAG agent over proprietary documents
Full control over chunking strategy, retrieval, and prompt engineering
Automating lead qualification with AI scoring
Visual workflow with AI node for scoring plus CRM update — no code needed
Multi-agent system with specialized roles
LangGraph provides the graph-based orchestration these architectures need
Need Help Deciding?
We implement both options. Tell us your use case and we'll recommend the right fit — then set it up for you.
Frequently Asked Questions
Can n8n replace LangChain?
For 80% of business AI automation, yes. n8n's AI nodes actually use LangChain under the hood. But for custom agent architectures, multi-agent systems, or fine-grained RAG pipelines, you'll hit n8n's ceiling and need LangChain directly.
Can I use both together?
Absolutely, and this is actually a common pattern. Build your custom AI agent in LangChain, expose it as an API endpoint, then orchestrate it alongside your business tools using n8n. Best of both worlds.
Which is faster to get to production?
n8n, by a wide margin. A working AI automation in n8n takes hours to days. A production-ready LangChain agent takes weeks to months. The gap narrows for complex use cases, but for standard business automation, n8n's time-to-value is unmatched.
Is LangChain overkill for most businesses?
Honestly, yes. We've seen startups spend months building LangChain agents that could have been n8n workflows. LangChain is the right choice when you need custom agent behavior that no visual tool can express. That's maybe 20% of the projects we see.
