Our customer's main use cases for n8n are extensive, as they are heavily utilizing it. n8n is clubbed with MCP, MCP protocols in terms of tracking, alerting, and automating some of the jobs, specifically in terms of billing, invoice generation, infrastructure monitoring, and downtime management; these are the areas where this platform is used.
External reviews
External reviews are not included in the AWS star rating for the product.
Incredible possibilities opened up
Adaptability and flexibility boost automation while offering room for optimization
What is our primary use case?
What is most valuable?
The most valuable features in n8n that I can highlight are its flexibility and ease to configure. Adaptation is pretty easy. It requires a little bit of programming skills, but comparatively, it's the shortest time window one can get comfortable with. People who have Python programming experience can get their comfort pretty easily.
Adaptability, scalability, and integrational flexibility are the top features at this point of time.
The capability of n8n to connect different applications and automate tasks while supporting over 200 pre-built integrations is pretty effective. So far, we have had all good positive thoughts about it. Our infrastructure teams are more vigilant about the security part and about data flow and data privacy at this point of time, but otherwise, the adaptation and flexibility of the tool is pretty good.
Regarding n8n supporting over 200 pre-built integrations, this capability contributes to the organization's communication in a pretty effective way.
I am familiar with the visual editor for designing workflows in n8n and it adds great value. It serves as a miniature digital twin framework to capture the existing as-is process flows. That design and visualization feature definitely adds a lot of value to the overall service portfolio.
The impact of real-time execution logs on optimizing the workflows is quite effective, but currently, the solutions we have prepared using this product are in a semi-production area only. We have not yet put it onto the production area.
What needs improvement?
What could possibly be improved in n8n to make this solution better for the next release is still a navigating process for us. I don't think I'm in a position to provide the improvement areas yet because we are still learning and discovering them.
Regarding the cost, scalability, and initial setup, I can think that for a bigger enterprise environment, the scalability, based on my observation, could be improved since we haven't fully explored that modular adaptive nature of n8n.
There are limitations in scalability.
For how long have I used the solution?
We have been working with n8n for more than six months now. We started using and exploring it around December.
What was my experience with deployment of the solution?
The deployment part is straightforward initially. If the environment grows and if n8n is scaled to the enterprise, customer-friendly plans would definitely help. Right now, it appears as a one-size-fits-all plan.
What do I think about the stability of the solution?
In terms of stability, n8n is pretty good; I don't see a challenge. I would rate it seven and above in stability.
What do I think about the scalability of the solution?
There are limitations in scalability. For scalability, I would rate n8n above seven, as we are still in the process of setting up the platform and configuring it.
How are customer service and support?
I have contacted tech support regarding n8n, but that is where we are struggling. We are not in SaaS platform mode of subscription, nor using a standard plan; instead, we are utilizing a customized plan of setting the server in our environment.
For the support rating, I would give it about a five; it's not too bad, but not too great either. It's acceptable.
How would you rate customer service and support?
Positive
Which solution did I use previously and why did I switch?
We do have good experience with other AI automation tools, mostly the open-source ones. Another open-source tool we are working with is make.com.
How was the initial setup?
Regarding the cost, scalability, and initial setup, for a bigger enterprise environment, the scalability, based on my observation, could be improved since we haven't fully explored that modular adaptive nature of n8n.
What was our ROI?
Our customers do see a return on investment with this solution; it absolutely offers value for money. One direct correlation is in terms of the amount of automation the tool provides, which directly impacts the number of people who can perform those tasks.
What's my experience with pricing, setup cost, and licensing?
For a small license part, I find n8n is reasonable. But the minute you expand, I believe it becomes a bit on the high side.
What other advice do I have?
I haven't had an opportunity to utilize the error management system. We haven't explored the security module features completely, so it wouldn't be fair to conclude in a generalistic way. Our teams are still exploring that module.
I would definitely recommend n8n to those who would want to use it, even though there are some challenges. It is one of the pretty effective products in the AI automation area, and it can grow leaps and bounds if some of these things are taken care of. It is pretty effective and one of the best tools I have seen.
On a scale of 1-10, I rate n8n an 8.
Which deployment model are you using for this solution?
If public cloud, private cloud, or hybrid cloud, which cloud provider do you use?
Great solution
A very efficient Automation tool for AI
I can't even call the delete method to delete it manually because the insert interface does not return the corresponding Id value.
I hope the official can update this part of the interface, because an effective RAG system relies heavily on this function.
2. I also saw that someone can complete the connection between vector and LLM through Code Node and LangChain Node. I hope the official can provide more documents to help users complete the connection.
2.Easier to use AI Agent
gmail
used n8n for automating calendar sync and for an AI MVP
Easy to use with credentials for power users.
Great AI Agent node.
The calling of sub workflows makes large/complex more manageable.