Developer tools are changing rapidly with AI. Therefore, companies that make AI easier in their workflows are attracting attention. After a startup called N8N (pronounced “Enay-Ten”) pivoted its workflow automation platform in 2022 to become AI-friendly, he said its revenue has increased five times, doubling its over the past two months alone.
Now, TechCrunch confirms that behind its growth, N8N has raised 55 million euros ($60 million) of valuation sources that are close to us as it is in the region of 250 million euros ($270 million).
Berlin-based N8N said the book currently has over 3,000 enterprise customers and roughly 200,000 active users. Startups will continue to invest in Tech using this Series B and expand in new markets like the US, with more than half of the N8N’s user base. The company does not disclose revenues, and its customer numbers include both free users and paid users, as well as those with short- and long-term subscriptions.
Highland Europe is leading this latest round, with HV Capital and former backers Sequoia, Felicis and Harpoon also taking part. Sequoia led the N8N seed round in 2020. Felicising Series A in 2021.
Founded in 2019, the startup has increased early traction from a team of developers who were looking for low-code and no-code automation solutions to make applications easier to sew without much tedious coding.
It also attracted attention for another reason. N8N built a reputation for being closely tied to the concept of a “fair code.”
Fair code is open source progression. Software developers use open source code for free, but if they want to commercialize works built on it, they will establish principles to supplement the open source creator or community. N8N founder and CEO Jan Oberhauser came up with the idea and runs a dedicated site for Fair Code.
But while N8N itself is built on fair code and grows with word of mouth leaning against the open source community, Github has over 70,000 “stars.”
AI, in particular, generate AI, clearly complements automation. It’s also used by competitors like Tines and Workato, like others in the broader world of automation like Uipath.
If automation and low-code approaches erase some of the busy work of putting together how different apps and services work, the generated AI brings even less technicality to the mix.
A year and a half ago Oberhauser said, “We could see this AI coming to us.” He quickly speculated that Sweetspot would incorporate it into the product and reduce the amount of work it took for developers to implement automation by turning instructions into natural language.
Here’s how Oberhauser explains: “It’s a prompt to build a workflow.” “People don’t need to write 50 lines of code to integrate the functionality of sending emails.” In natural language, you can write “get information from X and send it to Y.” “We think it’s worth changing it easier.”
The product is built with LLM blends in mind, and the idea is that if the end user is already building the service using one LLM, it can be exchanged to work on the N8N platform. And like many other developer-centric platforms, N8N has a rather extensive community of contributors active on platforms like GitHub, where they take part in the forums to help other developers ask questions, and build and use workflow templates built by others (N8N also has many workflow templates pre-built).
Despite all the hype and hopes of recent artificial intelligence and genai, the AI-driven version of the N8N was never featured at all. Then last year there was a sudden turning point.
why? It’s probably a weight that brings together some trends. There was a burst of chatter around AI in coding, and companies like poolside, cordum, magic all had been collecting big money from each other within months. And the chants that can help end users understand how to use AI have grown bigger.
But there’s a lot of hype and sometimes we talk about it there too. So, in the end, the ease and usefulness of N8N appears to be not only for dealing with users but also for investors.
“Everyone is trying to use AI, but they’re struggling to find practical use cases,” David Brygun, Highlands general partner who led the round, told me over the phone. “The design, scale and throughput of the N8N are what makes it possible for people to adopt it.”
Oberhauser admits that “it took a while for the market to catch up,” but says that around 75% of all N8N customers use AI tools they have built.
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