N8N and LangChain are similar, albeit distinct, AI workflow tools, so in this post, we’ll be discussing the differences between each tool.
Overview:
- What is n8n?
- What is LangChain?
- What is the difference between n8n and LangChain?
- Concluding thoughts.
What is n8n?
N8n is a workflow automation platform. Its features include the ability to re-run particular steps without having to re-do the entire workflow, fast debugging of code, the ability to replay or mock data, and over 1,700 templates available for use. It’s also visual and no-code, making it perfect for someone who wants to connect applications without coding experience.
What is LangChain?
LangChain is a platform for agent engineering, and the platform lets you pick whether you use a template or custom control to build your agent. Its features include visibility and control through every step of the process, fast adaptation through the building, testing, and deploying processes, flexible performance built for long-running workloads and human oversight, and model neutrality. It uses a Python/JavaScript framework for making applications with large language models (LLMs).
Speak About Digital describes more about both n8n and LangChain in his YouTube video, “LangChain vs. N8n (2025): What’s the difference?” He says LangChain is a library and coding toolkit for making particular AI-run brains. For instance, a programmer could use LangChain to write a program that could carry out a long conversation. recall what was said in the conversation, and use other tools to provide further information.
So, while n8n handles the automation, LangChain handles advanced AI thinking in specific tasks. If n8n is the manager that oversees the entire process, LangChain is its dutiful developer that takes care of the nitty-gritty, complex tasks.
What’s the difference between n8n and LangChain?
While n8n and LangChain both orchestrate AI models, they’re used in different scenarios.
For us here at Psycray, n8n is the backbone of all of our work. It helps us connect storage, crawlers, translations, indexers, and scheduled syncs. It also helps us with visual branching for guardrails and notifications. Lastly, it utilizes HTTP database, queue, and custom functions to link systems together.
While n8n is a powerful binding tool, it sometimes falls short when we need more control.
That’s where LangChain can step in and help. LangChain is a framework for connecting tools, data, and structured logic. It’s suitable for building a RAG chain – retrieval, prompt assembly, and output parsers.
In general, we use n8n for pipelines and operations and LangChain for serving queries inside an API or app.
Speak About Digital emphasizes that n8n and LangChain are not competitors; in fact, they can be used in tandem with each other.
As an example, he notes that if n8n received a text from a customer, it could send it to LangChain, which could take that text, process it, and come up with a thoughtful, empathetic reply. Once the reply is ready, LangChain could send it back to n8n, and n8n can take care of sending that reply back to the customer.
This example demonstrates how n8n can act as an overall automation manager helping everything run smoothly, while LangChain can aid in particular parts of the process that require deeper thinking.
Conclusion
Both n8n and LangChain are wonderful AI model tools. While n8n is a workflow automation tool that takes an overarching approach to the system, LangChain is an agent engineering tool that can handle more control-oriented tasks. The tool you choose will depend on your needs and resources.
We hope you found this post informative. If you’re interested in our AI agentic solutions, please feel free to reach out to us. We’d love to hear from you regarding how we can help you reach your business goals using AI.