n8n Revenue: How n8n Grew to $100M ARR and a $5.2B Valuation
n8n crossed a reported $100M ARR in 2026 and SAP invested at a $5.2B valuation. See its revenue and user timeline and how templates and AI drove growth
n8n grew by giving technical users more control than simple no-code tools, letting them self-host the product for free, and turning its community into a distribution engine.
Users built integrations, shared workflow templates, answered questions, and made tutorials. n8n then made money from teams that wanted hosted infrastructure, collaboration, security, governance, and support.
That engine was already working when generative AI arrived. n8n moved early and let users build AI applications inside the same workflow canvas. Its old strengths (integrations, credentials, logic, logs, and reliable execution) became the parts companies needed to put AI agents to work.
The result was a sharp change in growth. n8n said its users grew 6× and its revenue grew 10× during 2025. By May 2026, it reported 1.7 million monthly active builders and more than 1,400 enterprise customers. When SAP invested in May 2026, n8n investor HV Capital said the company had crossed €100 million in annual recurring revenue.
That $100 million figure is reported ARR, not audited annual revenue. But the larger story is clear: n8n spent six years building product depth and community distribution, then caught the AI-agent wave with the right product at the right time.
n8n's growth in one table
| Date | Milestone | Why it mattered |
|---|---|---|
| 2018 | Jan Oberhauser began building n8n | The product started from a problem he had faced himself |
| June 2019 | The first public version appeared on GitHub | Developers could try, inspect, change, and self-host it |
| October 2019 | n8n launched on Hacker News and Product Hunt | It reached a wider technical audience and attracted investors |
| November 2019 | n8n reached 10,000 GitHub stars | Early demand was visible before the company had a cloud product |
| March 2020 | n8n raised a $1.5 million seed round | The company could hire its first team |
| January 2021 | n8n Cloud launched | Free adoption gained a simple path to paid usage |
| April 2021 | n8n raised a $12 million Series A | It reported 16,000+ community members and 200+ app connectors |
| October 2023 | The LangChain integration launched in beta | Users could build AI applications and agents inside n8n |
| March 2025 | n8n raised a €55 million Series B | The company reported more than 200,000 users |
| October 2025 | n8n raised $180 million at a $2.5 billion valuation | It reported 6× user growth and 10× revenue growth during 2025 |
| May 2026 | SAP invested at a $5.2 billion valuation | n8n reported 1.7 million monthly active builders and 1,400+ enterprise customers |
| May 2026 | HV Capital, an n8n investor, said n8n had crossed €100 million ARR | This is the latest specific ARR figure found for this article |
Sources: n8n's early history, Series A announcement, Series B announcement, Series C announcement, SAP investment announcement, and Product School's founder interview.
1. n8n started with a narrow problem the founder knew well
Before n8n, founder Jan Oberhauser worked in visual effects and built tools for artists. Later, he kept running into the same problem at a startup: even a small automation took hours to make reliable.
The script itself was only one part of the work. He also had to read API docs, deploy it, set up SSL, report errors, and make sure it restarted after a crash.
Oberhauser began building n8n in 2018. The name came from “nodemation,” a blend of “node” and “automation.”
He published the first version on GitHub in June 2019 and shared it on AlternativeTo and Quora. People began filing issues, sending emails, and contributing code.
This gave n8n an early advantage: it was built for a real problem, and its first users could help shape the solution.
2. It did not try to become a cheaper Zapier
The automation market already had simple tools. n8n chose a different position.
Its main promise was control.
Users could self-host it. They could inspect and change the code. They could write JavaScript, make API requests, add custom nodes, and build workflows with branches, loops, and unusual logic.
This made n8n harder to learn than some no-code tools. It also made the product useful after a workflow became complex.
That distinction mattered. Many visual tools are easy for the first 80% of a job. The last 20% often needs code, a custom API call, or deeper control. n8n accepted a steeper learning curve so technical users would not have to leave the product when they hit that point.
The company was not selling simplicity alone. It was selling speed without giving up flexibility.
3. Free self-hosting became the top of the funnel
n8n launched without a hosted product. Users had to run it on their own servers.
That created work, but it also removed a large barrier to adoption. A developer could try the whole workflow engine without booking a demo, asking for a budget, or sending company data to a new vendor.
Self-hosting was especially attractive to technical teams that cared about data control, privacy, or custom infrastructure.
The source code was visible, but n8n was not open source under the Open Source Initiative's definition. It used a commercial restriction from the start and later adopted its Sustainable Use License. The license allows internal business use and self-hosting, but it limits selling n8n itself as a hosted service or embedding it in a commercial product without an agreement.
The accurate terms are source-available or fair-code.
This choice let n8n use a free product for distribution while protecting its ability to sell hosting and commercial licenses.
The approach produced early attention. n8n reached 5,000 GitHub stars within five months and 10,000 by November 2019, according to the company's second-anniversary history.
4. Hacker News and Product Hunt brought the first wave of users
Oberhauser waited until October 2019 to launch n8n to a wider audience.
The Hacker News launch received hundreds of points and comments. n8n also finished first on Product Hunt that day.
The discussion was not all positive. Some people objected to calling n8n open source because its license included commercial limits. The criticism pushed the company to explain its fair-code model more clearly.
But the launch did three useful things:
- It put n8n in front of technical users who had the problem.
- It produced feedback and code contributions.
- It gave investors visible proof of demand.
TechCrunch later reported that this early activity helped bring n8n to the attention of Sequoia and firstminute capital, which co-led its $1.5 million seed round in March 2020.
The launches did not create the whole company. They gave a useful product its first concentrated burst of attention.
5. Community contributions made the product more useful
Automation products become more valuable as they connect to more tools. But one startup cannot build every integration people need.
n8n let its users help.
An early user, Ricardo Espinoza, found n8n on Product Hunt and needed a Mandrill integration. He built it himself. Oberhauser reviewed the work and answered questions. Espinoza kept contributing and eventually built around 60 integrations before joining the company.
This created a product loop:
more users → more integrations and fixes → more useful workflows → more users
By November 2020, 100 people had contributed to the repository. By the April 2021 Series A, n8n reported more than 16,000 community members, 13,000 GitHub stars, and connectors for more than 200 apps.
The community also wrote documentation, answered support questions, and showed people what to build. This allowed n8n to expand faster than its team could have done alone.
6. n8n Cloud turned free usage into revenue
The free product created adoption, but self-hosting came with work. Users had to manage servers, updates, backups, security, and uptime.
n8n Cloud entered early access in December 2020 and launched in January 2021. It offered the same core workflow engine without the setup and maintenance.
This gave n8n a clear business model:
- Community Edition: free self-hosting for people who want control and can manage the infrastructure.
- n8n Cloud: paid hosting for people who want convenience.
- Business and Enterprise: paid features for collaboration, security, governance, scale, and support.
- Embed: commercial licensing for companies that want to put n8n inside their own products.
The free edition did not compete with the paid product as much as it fed it. People learned n8n on their own. Some later paid when the cost of running it, sharing it, or governing it became higher than the subscription.
7. Templates turned user work into search traffic
Workflow templates made n8n easier to start using. They also became a large acquisition channel.
A template is a working page for a specific task, such as:
- sending Gmail messages to Slack
- qualifying leads with an AI model
- saving form responses in Google Sheets
- building a Telegram support agent
- summarizing documents with OpenAI
Each page can rank for a narrow search. A person finds the workflow through Google, imports it, connects their accounts, and becomes an n8n user.
The same template can also appear in a YouTube tutorial, a blog post, a social post, or a community discussion.
As of September 12, 2026, n8n's public library listed 12,326 workflow templates. Its separate integrations directory listed 2,174 entries, including apps, triggers, core nodes, and AI components. These are live directory counts, not customer numbers.
This created a second loop:
user builds a workflow → publishes a template → template ranks or gets shared → new user imports it → new user builds another workflow
n8n did not have to write every long-tail landing page itself. Its users supplied much of the underlying knowledge.
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8. Affiliates and creators taught the product for n8n
n8n has a learning curve. That makes education part of the product's distribution.
Creators publish videos and articles such as “How to build an AI sales agent with n8n.” The content explains the use case, shows the product, and gives viewers a reason to try it.
n8n strengthened this behavior with an affiliate program that pays 30% of n8n Cloud referral revenue for 12 months. The company encourages affiliates to make YouTube videos, write blog posts, and publish templates.
The incentives line up:
- Creators get views, authority, clients, or affiliate income.
- Users get free education and ready-made workflows.
- n8n gets distribution without producing every tutorial itself.
n8n says much of this influence happens on YouTube, Discord, social media, and group chats, which makes the full effect hard to measure. Its 2026 community research described users teaching one another as a core part of the flywheel.
9. The AI bet looked weak before it looked obvious
AI was not part of the original plan.
In 2022, Oberhauser began to worry that AI assistants might replace the simpler automations people built with n8n. Adding a small AI feature would not be enough. He wanted n8n to become a place where users could build AI applications.
After ChatGPT launched, Oberhauser and two engineers built the first version in about eight weeks, according to a 2026 founder profile from Felicis.
The launch was underwhelming. Some users feared that n8n was replacing the automation product they liked. It took close to a year of product work, teaching, and clearer messaging for the community to accept the direction.
n8n's LangChain integration launched in beta in October 2023. It let users combine models, memory, vector databases, agents, and existing n8n tools inside one workflow.
During 2024, n8n added support for more models, AI nodes, agents, vector stores, chat triggers, and a self-hosted AI starter kit. It also increased its YouTube output, restarted community events, launched a newsletter, and created an ambassador program. The company described these changes in its 2024 review.
Then the market caught up.
People moved from asking an AI model questions to asking it to take actions. An agent needed access to email, calendars, CRMs, databases, APIs, and internal tools. It also needed credentials, branching, retries, logs, tests, and human approval.
n8n had spent years building those parts.
10. AI gave n8n a much bigger story
Before AI, n8n helped technical users build flexible automations.
After the shift, it could help teams connect models to real business systems and run AI agents in production.
This was more than a change in marketing. n8n became part of the AI application itself.
Its model-neutral approach also helped. Users could change the LLM, database, vector store, or business app without rebuilding the whole workflow system. That was useful in a fast-moving market where no one knew which AI stack would win.
The growth followed:
- In March 2025, n8n said it had more than 200,000 users.
- In October 2025, it reported 6× user growth and 10× revenue growth during the year.
- Felicis later reported that more than 80% of workflows built in 2025 involved AI agents.
- In May 2026, n8n reported 1.7 million monthly active builders and more than 1,400 enterprise customers.
These are company or investor figures, not independently audited measurements. They still show where the inflection happened: years of steady automation growth were followed by a much faster AI-agent phase.
11. n8n stopped forcing marketing toward lead targets
n8n's marketing team had two goals: drive adoption and generate leads.
The company was naturally good at adoption. But when lead targets fell short, effort moved away from community work and toward short-term lead generation.
Oberhauser believed this weakened the channel that made n8n different. The company removed the lead goal and focused on adoption inside large organizations. It invested more in community events, education, content, and creators.
In a Sequoia interview, Oberhauser explained that the effect was delayed. The strategy needed time for more people to create content, for that content to rank, and for the wider market to understand n8n as an AI tool.
This is an important part of the growth story. n8n did not treat free users as an audience that sat outside the enterprise business. Free builders were often the people who introduced the product inside large companies.
12. Bottom-up adoption opened the enterprise market
n8n's enterprise motion often began with one technical user.
That person could test Community Edition, prove a use case, and share the workflow with colleagues. As usage spread, the company needed better permissions, shared credentials, monitoring, separate environments, security controls, and support.
That created a natural path from free use to an enterprise contract.
The Stepstone case study shows the pattern. One engineer began using Community Edition in 2021. Four years later, Stepstone had hundreds of workflows and moved to Enterprise as ownership, credentials, and monitoring became harder to manage. n8n says the company now runs more than 700 production workflows.
This is a vendor case study, so it should not be treated as independent proof. But it gives a clear example of n8n's land-and-expand path:
individual experiment → team adoption → production use → paid governance
SAP's May 2026 investment made the enterprise direction even clearer. SAP agreed to embed n8n inside Joule Studio, and the transaction valued n8n at $5.2 billion. n8n said the deal would bring its workflow layer closer to the systems large companies already use.
How n8n's growth loops work together
n8n did not grow from one channel. Several loops reinforced one another.
| Growth loop | How it worked |
|---|---|
| Free product loop | Self-hosting reduced the cost and risk of trying n8n |
| Community loop | Users contributed code, nodes, fixes, support, and ideas |
| Integration loop | More connections created more possible use cases |
| Template and SEO loop | Shared workflows became useful pages for narrow searches |
| Creator loop | Tutorials taught the product and sent new users into the community |
| Affiliate loop | Referral revenue gave creators another reason to publish |
| Cloud loop | Users who wanted convenience paid n8n to host the product |
| Enterprise loop | Bottom-up use created demand for governance, security, and support |
| AI loop | More AI use cases created more templates, tutorials, integrations, and enterprise demand |
The key was sequence.
n8n built the product and community first. It added cloud monetization without removing free self-hosting. It expanded through templates and creators. Then it used that entire base to move into AI agents and enterprise orchestration.
What founders can learn from n8n
Build around a real constraint
n8n did not begin with a broad claim about changing work. It began with a simple pain: small automations took too long to deploy and maintain.
Pick a wedge that creates strong preference
n8n was not the easiest tool for everyone. It was unusually flexible for technical users. That gave a smaller group a strong reason to choose it.
Let the free product feed the paid product
Free self-hosting built trust and familiarity. Cloud sold convenience. Enterprise sold control at scale.
Turn user output into acquisition
Integrations, templates, tutorials, and forum answers were useful to current users and discoverable by future users.
Reward people who teach the product
Affiliates, ambassadors, and creators helped n8n explain a product that could not be understood from a short landing page alone.
Prepare before the market is ready
n8n's first AI release did not take off. The company kept building until demand for agents caught up with the product.
Do not abandon the channel that already works
n8n's community was not a soft brand project. It was product development, support, education, acquisition, and enterprise distribution at the same time.
The real reason n8n grew
n8n was well positioned when AI agents became popular, but timing alone does not explain its growth.
By then, the company already had:
- a free way for developers to start
- a product that handled complex workflows
- hundreds of app connections
- years of community trust
- thousands of templates and tutorials
- a hosted product that could convert free demand
- an enterprise product for security and governance
AI made each part more valuable.
Models could reason, but they still needed tools and reliable execution. n8n already connected those tools and made the workflow visible. The company did not have to invent a new distribution engine when the market changed. It gave its existing engine a much larger use case.
That is the simplest explanation for how n8n grew: community-led distribution built the base, cloud and enterprise captured the value, and AI agents turned years of workflow infrastructure into a fast-growing platform.
Frequently asked questions
How did n8n grow?
n8n grew through free self-hosting, a strong developer community, user-built integrations, workflow templates, creator education, paid cloud hosting, and bottom-up enterprise adoption. Its early move into AI agents made those channels much more valuable.
When was n8n founded?
Jan Oberhauser began building n8n in 2018 and published the first public version on GitHub on June 23, 2019.
Is n8n open source?
Not under the Open Source Initiative's definition. n8n is source-available under a fair-code Sustainable Use License. Users can self-host it for internal use, but the license restricts selling n8n as a service or embedding it commercially without an agreement.
How does n8n make money?
n8n makes money from its hosted cloud product, paid self-hosted Business and Enterprise plans, and commercial embedding agreements. Paid plans offer convenience, collaboration, governance, security, scale, and support.
What is n8n's ARR?
n8n investor HV Capital said in May 2026, when SAP invested, that n8n had crossed €100 million in annual recurring revenue. Product School repeated the milestone in July 2026. n8n is private, and the figure has not been audited publicly. ARR is also different from recognized annual revenue.
Why did AI accelerate n8n's growth?
AI agents need to connect models with apps, data, credentials, logic, approvals, and logs. n8n had already built those parts for normal workflow automation. It could turn them into an orchestration layer for AI without starting from zero.
How many users does n8n have?
n8n reported 1.7 million monthly active builders in May 2026. “Builders” is the company's term, and it should not be read as the number of paying customers.
What is n8n's valuation?
SAP's investment in May 2026 valued n8n at $5.2 billion. As part of the deal, SAP agreed to embed n8n inside Joule Studio.
A note on the numbers
n8n is a private company. Most usage and revenue figures in this article come from n8n, its investors, or interviews with its founder. They are useful but not independently audited.
The reported $100 million ARR is not the same as $100 million in recognized annual revenue. ARR annualizes recurring contracts or subscriptions at a point in time. n8n has not published the details of its calculation.
Live counts for GitHub stars, templates, integrations, and community members also change often. This article was last checked on September 12, 2026.
Sources
Primary sources
- Celebrating n8n's second anniversary — n8n
- Original n8n launch discussion — Hacker News
- n8n's Series A announcement — n8n
- n8n Cloud early-access announcement — n8n Community
- Sustainable Use License announcement — n8n
- n8n Version 1.0 — n8n
- n8n's 2024 review — n8n
- n8n's €55 million Series B — n8n
- n8n's $180 million Series C — n8n
- SAP's strategic investment in n8n — n8n
- n8n community research — n8n
- n8n workflow template directory — n8n
- n8n integrations directory — n8n
- n8n affiliate program — n8n
- Stepstone case study — n8n
Interviews and reporting
- Jan Oberhauser on building the universal AI automation layer — Sequoia Capital
- How Jan Oberhauser and n8n became essential to the AI revolution — Felicis
- The AI product rule that grew n8n to $100M ARR — Product School
- HV Capital on n8n's $5.2B valuation and €100M+ ARR, HV Capital
- n8n's $1.5 million seed round — TechCrunch
- n8n's $12 million Series A — TechCrunch
- n8n's €55 million Series B — TechCrunch