What is n8n? Complete History: Workflow Automation, Fair-Code, AI Agents, LangChain & More (2026)

Introduction

n8n burst onto the developer scene in October 2019 with a radical premise: what if workflow automation was powerful enough for engineers, transparent enough to inspect, and free enough to self-host? Founded by Jan Oberhauser — a former VFX artist who worked on Hollywood blockbusters like Maleficent and Happy Feet Two — n8n grew from a scrappy Berlin side project into a $2.5 billion automation platform with 150,000+ GitHub stars, 230,000+ active users, and the backing of Sequoia, Accel, and NVIDIA.

But the story of n8n is not a simple tale of open-source triumph. It is a story about licensing controversies, an AI pivot that supercharged growth by 5.5x in a single year, critical security vulnerabilities that shook the self-hosting community, and a founder who wants to build the "Excel of AI" and take it public on a European stock exchange. This article explores the complete history of n8n, from a VFX pipeline to a $2.5 billion unicorn, and asks the question that every automation team is thinking: is n8n the future of AI-powered workflow automation?

🤖 What Is n8n?

n8n (pronounced "n-eight-n") is a workflow automation platform that lets users connect apps, services, and AI models through a visual node-based interface. The name is short for "nodemation" — a portmanteau of "node" and "automation" — following the same abbreviation convention as k8s (Kubernetes) and i18n (internationalization).

At its core, n8n works like a visual programming environment. You drag nodes onto a canvas, each representing a service or action (Slack, Gmail, a database query, an AI model call), and connect them with wires to define the flow of data. When a trigger fires — a new email, a webhook, a scheduled time — the workflow executes node by node, transforming and routing data through your pipeline.

"I always felt frustrated that smart, capable people always depended on pipeline engineers like me to automate their workflows. I wanted to build something that would change that."

Jan Oberhauser, Founder & CEO of n8n

What sets n8n apart from competitors like Zapier and Make is its source-available, self-hostable architecture. You can run n8n on your own servers, inspect every line of code, and extend it with custom nodes — all without paying per-execution fees. This resonated deeply with developers and DevOps teams who wanted automation without vendor lock-in.

The platform has since evolved far beyond simple task automation. With the introduction of AI agent nodes powered by LangChain, n8n has become a popular platform for building AI workflows — connecting frontier language models to real-world tools and data sources through a visual interface. This AI pivot transformed n8n's trajectory, driving revenue from $7.2M to $40M ARR in a single year and catapulting its valuation from $350M to $2.5B in four months.

🥚 The History of n8n

From VFX Studios to Pipeline Engineering

The story of n8n starts not in a Silicon Valley garage or a Berlin coworking space, but on the set of a Hollywood movie.

Jan Oberhauser has a background that's unusual for a tech CEO. He didn't study computer science — he studied Audiovisual Media at the Hochschule der Medien (Stuttgart Media University) from 2005 to 2009. After graduating, he landed a career in visual effects, working at Academy Award-winning VFX studios on major productions including Disney's Maleficent and the animated sequel Happy Feet Two.

"I come from the movie side of things. I did effects for movies. Originally I worked on the actual effects and then later became a pipeline TD — it was my job to make the life of the artists more efficient and easier, which obviously involved a lot of automation."

Jan Oberhauser, Accel Spotlight On (2025)

VFX production is, at its core, a massive data pipeline problem. Every shot passes through dozens of artists, each using different software tools, with files flowing between departments in carefully orchestrated sequences. The people who make this chaos manageable are pipeline engineers — the unsung heroes of film production who write scripts and build tools to automate the flow of assets, renders, and reviews.

Oberhauser became one of those pipeline engineers. And in doing so, he noticed something that would change his career:

"Those people — very smart, very well paid, and quite technical — they were always reliant on me or other people like myself to actually do the things they wanted done. They could have had so much more impact if they would have been empowered. And they weren't."

This wasn't just frustration — it was the origin thesis for n8n. The insight that smart people were bottlenecked by their dependency on engineers would become the philosophical foundation for everything Oberhauser built next.

One company in particular gave him proof that the idea could work. At Digital Domain, the VFX studio co-founded by James Cameron, they already had an internal automation solution — but it was XML-based. "Literally no non-technical person would have ever used it," Oberhauser recalled. "But it gave me the understanding that something is actually possible."

The seed was planted. What if there was a tool that let non-engineers build their own automations — one that was powerful enough for real production use but accessible enough that you didn't need a pipeline engineer to run it?

The VFX industry, despite its glamorous output, is one of the most process-heavy creative fields in existence. A single frame of a Marvel movie might pass through modeling, texturing, rigging, animation, lighting, compositing, and rendering — each step producing files that need to be tracked, versioned, and routed to the next department. Pipeline engineers build the invisible scaffolding that keeps this machine running.

What Oberhauser realized was that this bottleneck wasn't unique to VFX. Every industry — finance, healthcare, marketing, logistics — had its own version of the pipeline problem. Smart people doing repetitive manual work because the automation tools were either too technical (writing scripts) or too limited (existing no-code tools couldn't handle complex workflows).

The question wasn't whether people needed better automation. It was whether someone could build a tool that was powerful enough for engineers yet accessible enough for everyone else.

The Side Project That Changed Everything (2018-2019)

Oberhauser started building n8n as a side project in 2018 while working at another startup. The initial concept was straightforward: a visual, node-based automation tool where you could connect different services and define workflows by dragging and dropping nodes on a canvas.

But the motivation ran deeper than building another SaaS product. As Oberhauser explained in his Accel Spotlight On interview:

"I realized that I actually spent probably 90% of my time reimplementing things that have been implemented before. Get something from GitHub, send a message to Slack — each of those pieces have been literally implemented millions of times before. All the businesses I was at, all the projects I worked on... the same thing. And the same is true for other people."

The insight was that automation wasn't just a VFX problem — it was a universal tax on every knowledge worker in every industry. The same integrations, the same data transformations, the same glue code — rebuilt from scratch millions of times over.

For a year and a half, Oberhauser coded n8n in his spare time — evenings and weekends while holding down his day job and caring for his wife and young child. The building metaphor he kept returning to was Lego: he wanted to create modular, snap-together building blocks for automation. Each node would be a self-contained Lego brick — an API call to Slack, a database query, a file transformation — that you could connect with other bricks to build anything.

The technical architecture reflected this philosophy. n8n was built with TypeScript on Node.js, with a Vue.js frontend that rendered workflows as interactive flowcharts. Each node encapsulated a specific integration, and data flowed between nodes through connections you drew on the canvas.

On June 23, 2019, Oberhauser created the n8n GitHub repository, making the source code publicly available. He incorporated n8n GmbH in Berlin, Germany — choosing to build his company in Europe rather than relocating to San Francisco, a decision that would later inform his ambition for a European IPO.

The timing was prescient. The automation market was dominated by Zapier (founded 2011) and Integromat (later Make), but both were closed-source, cloud-only platforms with per-task pricing that could get expensive quickly. Developers wanted an alternative they could self-host, inspect, and extend.

n8n was that alternative.

The design philosophy was deliberate. Oberhauser didn't want to build another "easy" tool that would hit a ceiling the moment users needed real power. Instead, he designed n8n as a "low floor, high ceiling" platform — simple enough to get started with drag-and-drop, powerful enough to handle enterprise-grade automation with custom JavaScript functions, error handling, branching logic, and sub-workflows.

This philosophy — accessibility without sacrificing power — would become n8n's defining characteristic and the key reason it attracted a passionate developer community.

The Launch: Product Hunt, Hacker News, and Instant Controversy (October 2019)

In October 2019, Oberhauser launched n8n on Product Hunt and Hacker News. The response was immediate and polarizing.

On Product Hunt, n8n positioned itself as an "open-source" alternative to Zapier. Developers loved the concept — a self-hostable automation tool with a visual interface and growing integration library. The launch generated significant buzz, and the GitHub repository quickly accumulated stars.

But there was a problem.

When n8n hit Hacker News, eagle-eyed open-source advocates noticed that n8n's license wasn't actually open source in the traditional sense. The software was published under the Apache 2.0 license with a Commons Clause restriction, which prohibited using n8n to provide a commercial hosted service. This meant you could self-host n8n for your own use, but you couldn't build a competing SaaS product on top of it.

The backlash was swift. A GitHub issue — now infamous as Issue #40 — was filed with the title: "N8n is not open source and your project is gaslighting its users."

The issue argued that calling n8n "open source" while using a license that restricted commercial use was misleading and harmful to the open-source movement. The debate was heated, passionate, and touched on deep philosophical questions about software freedom, sustainable business models, and what the term "open source" actually means.

Oberhauser's response was pragmatic. Rather than doubling down on the "open source" label or switching to a permissive license, he coined a new term: fair-code.

"We wanted to create something in between open source and proprietary software. We call it fair-code — the source code is available, you can use and modify it freely, but you can't sell it as a hosted service competing with us."

In a later interview, Oberhauser was even more candid about the business reality behind the licensing decision:

"I'm not building n8n for free because I'm a good person. I genuinely need to build a sustainable company. The source-available model means we get the distribution benefits of open source and the community contributions, but we also get to run a real business."

This bluntness was characteristic. Where other founders might have wrapped the licensing in idealistic language, Oberhauser acknowledged the commercial logic openly — earning respect from pragmatic developers even as it frustrated open-source idealists.

The fair-code concept would remain controversial, but it carved out a defensible position. n8n's code was public and inspectable. You could self-host it for free. You could modify it for your needs. You just couldn't turn around and sell it as a competing cloud service.

By late 2019, n8n had already accumulated roughly 10,000 GitHub stars — a remarkable achievement for a tool that was barely a few months old.

The Issue #40 debate, while uncomfortable, ultimately helped n8n. It established the company's licensing position clearly and early, forcing Oberhauser to articulate a coherent philosophy about software freedom and business sustainability. And it generated enormous attention — there's no better marketing for a developer tool than a passionate Hacker News debate about licensing.

The fair-code concept also spawned a broader movement. Oberhauser created the faircode.io website to define the principles and invite other companies to adopt similar models. While the term never achieved the ubiquity of "open source," it gave a name to a licensing approach that many companies were already gravitating toward.

Sequoia Comes Calling: The Seed Round (March 2020)

The GitHub stars and developer buzz caught the attention of some of the most prestigious venture capital firms in the world.

In March 2020, n8n closed a $1.5 million seed round co-led by Sequoia Capital and firstminute capital. For a Berlin-based startup with a single founder and a product that had been public for less than six months, getting Sequoia on the cap table was a remarkable signal.

Sequoia's investment wasn't just about the product — it was about the market dynamics. The automation space was growing rapidly, and the cloud-only incumbents left a massive gap for developer-focused, self-hostable tools. n8n's source-available model created a powerful distribution flywheel: developers discovered n8n, self-hosted it, fell in love with it, and then advocated for their companies to adopt n8n Cloud for production workloads.

This is the same go-to-market motion that had worked for companies like GitLab, Elastic, and MongoDB — give the product away, build a community, and monetize through enterprise features and managed cloud services.

n8n Cloud and the Series A (2021)

With seed funding secured, Oberhauser's team spent 2020 building out the product and growing the community. On December 30, 2020, n8n shipped its 100th release — a testament to the rapid pace of development.

January 2021 marked a crucial inflection point: the launch of n8n Cloud, a managed SaaS version of n8n that let users run workflows without managing their own infrastructure. This was the commercial engine that would fund n8n's growth — free self-hosting for individuals and small teams, paid cloud service for companies that wanted reliability, support, and zero ops burden.

The same year, n8n launched n8n.embed, which allowed companies to embed n8n's workflow builder directly into their own products. This expanded n8n's reach beyond standalone automation into a white-label integration layer that other SaaS platforms could leverage.

In April 2021, n8n raised a $12 million Series A led by Felicis Ventures. The round validated the dual business model of self-hosted community edition plus managed cloud service, and provided fuel for hiring and integration development.

The timing of the Series A was significant. By early 2021, the pandemic had accelerated digital transformation across industries. Companies that had relied on manual processes were suddenly forced to automate — and tools like n8n, Zapier, and Make saw a surge in adoption. Remote work meant distributed teams needed automated handoffs between tools, and n8n's self-hostable model was particularly attractive to companies in regulated industries (healthcare, finance, government) where sending workflow data through third-party cloud services was a non-starter.

The License Shift: Sustainable Use License (March 2022)

On March 17, 2022, n8n made a significant licensing change, moving from its original Apache 2.0 + Commons Clause setup to the Sustainable Use License, a custom license based on the Elastic License 2.0.

The Sustainable Use License preserved the core principles of fair-code: anyone could view, use, modify, and redistribute n8n's source code for free, but offering n8n as a hosted commercial service was prohibited. The new license was cleaner, better defined, and aligned with the emerging trend of source-available licenses adopted by companies like Elastic, MongoDB, and Redis.

The licensing change reflected a broader shift in the infrastructure software industry. Cloud providers, particularly AWS, had a history of taking open-source databases and tools, wrapping them in managed services, and profiting without contributing back. The Sustainable Use License was n8n's defense against this dynamic — keep the code public but protect the hosted service business.

Not everyone was convinced. Open-source purists continued to argue that any license restricting commercial use wasn't truly "open" — and the fair-code label was just marketing spin for a proprietary license. But for pragmatic developers who primarily wanted to self-host and tinker, the distinction was largely academic.

The Broader Licensing Debate

n8n's licensing journey is part of a much larger story in the software industry. Throughout the late 2010s and early 2020s, a wave of companies abandoned traditional open-source licenses in favor of source-available alternatives:

• MongoDB switched from AGPL to the Server Side Public License (SSPL) in 2018, specifically to prevent AWS from offering MongoDB as a service
• Elastic (Elasticsearch) moved from Apache 2.0 to SSPL + Elastic License in 2021, prompting AWS to fork the project as OpenSearch
• Redis added Commons Clause restrictions, then switched to dual licensing under RSAL and SSPL
• HashiCorp (Terraform) switched from MPL to the Business Source License (BSL) in 2023, triggering the OpenTofu fork

n8n's adoption of the Sustainable Use License placed it squarely in this trend. The pattern was consistent: companies built powerful software, attracted large communities, and then realized they needed to protect their commercial business from cloud providers who could take the software, wrap it in a managed service, and capture all the value.

The debate remains unresolved. The Open Source Initiative maintains that only OSI-approved licenses qualify as "open source." Companies like n8n argue that the binary distinction between "open source" and "proprietary" doesn't capture the nuance of source-available, community-friendly licenses that nonetheless protect sustainable business models.

For n8n specifically, the licensing approach has worked remarkably well. The source code remains public. Self-hosting remains free. The community continues to grow. And the company has built a viable commercial business through n8n Cloud. Whether you call it "fair-code," "source-available," or something else, the model has delivered on its core promise: transparency without self-destruction.

n8n 1.0: Production Ready (July 2023)

After four years of rapid iteration, n8n reached a major milestone in July 2023 with the release of n8n 1.0 — the first version the team considered truly production-ready.

The 1.0 release signaled stability and maturity. Enterprise teams that had been experimenting with n8n for internal automations now had a version they could confidently deploy in production environments with long-term support expectations.

By this point, n8n had grown to over 200 integrations, with a thriving community contributing custom nodes, templates, and tutorials. The platform was becoming the default choice for technical teams who needed automation power beyond what Zapier's no-code interface could provide.

But the biggest transformation was still ahead.

The Complete Product Timeline

Before diving into n8n's AI transformation, it's worth stepping back to see the full arc of product development:

Six years. From zero to $2.5 billion. From a single developer in Berlin to a platform used by 25% of the Fortune 500.

The timeline is compressed, but the story is actually one of patient execution punctuated by a single, dramatic inflection point: the AI pivot. Understanding both phases — the steady infrastructure building and the explosive AI growth — is essential to understanding where n8n is headed next.

🧠 The AI Pivot: From Workflow Tool to "Excel of AI"

AI Nodes and the LangChain Integration (2024)

The release that changed n8n's trajectory wasn't a point upgrade or a new pricing tier. It was the introduction of AI agent nodes in 2024, powered by LangChain under the hood.

But the pivot didn't begin with confidence. It began with fear.

When ChatGPT launched in late 2022, Oberhauser had an existential reaction. As he recalled in his "Building the Universal AI Automation Layer" interview:

"I was scared. I genuinely thought: is this going to make n8n obsolete? If AI can just do everything, do you still need a workflow automation tool?"

The turning point came when Oberhauser started mapping the AI value chain — not as a consumer, but as an infrastructure builder. He looked at companies like Pinecone (vector databases) and realized they were worth billions not because they built AI models, but because they built the plumbing around AI models. n8n was already plumbing. The insight crystallized: n8n didn't need to compete with AI — it needed to become the connective tissue that made AI useful in the real world.

The team moved fast. Oberhauser and what he described as "myself and one and a half other developers" built the first AI integration in approximately six weeks. The speed was possible precisely because n8n's modular, node-based architecture was already designed for exactly this kind of extension — each AI capability was just a new node that snapped into the existing canvas.

LangChain is a framework for building applications with large language models (LLMs). It provides abstractions for connecting LLMs to tools, data sources, and memory systems — exactly the kind of orchestration that n8n's visual workflow builder was designed to handle.

The integration was natural. n8n's node-based architecture mapped almost perfectly onto LangChain's concept of chains and agents. Each LangChain component — a model call, a tool invocation, a memory retrieval — could be represented as a node in n8n's visual canvas, connected with wires that defined the flow of data and decisions.

The AI nodes supported:

• Frontier LLMs: OpenAI GPT-4o, Anthropic Claude, Google Gemini, and more
• RAG (Retrieval-Augmented Generation): Connect vector stores like Pinecone, Supabase, Weaviate, and Qdrant for grounded, context-aware AI responses
• Tool-calling: Let AI agents invoke any of n8n's 400+ integrations as tools
• Memory persistence: Maintain conversation and task context across workflow executions
• AI Agent nodes: Build autonomous agent workflows that can reason, plan, and execute multi-step tasks

This wasn't just a feature addition — it was a platform transformation. n8n went from "Zapier alternative for developers" to "the visual platform for building AI agent workflows."

How n8n AI Workflows Actually Work

To understand why n8n's AI capabilities resonated so deeply, consider a concrete example: building an AI-powered customer support agent.

In a traditional Zapier workflow, you might connect a new email trigger to a GPT action to a Slack notification. Simple, linear, and limited.

In n8n, you can build something far more sophisticated:

1. Trigger: A customer support ticket arrives via webhook
2. Classification: An AI agent node analyzes the ticket and classifies it by category, urgency, and sentiment
3. RAG Retrieval: The workflow queries a Pinecone vector store containing your knowledge base to find relevant documentation
4. Draft Response: A second AI agent node takes the classification and relevant docs and drafts a response
5. Human Review: The draft is posted to Slack for agent approval
6. Conditional Routing: Based on urgency, the workflow either sends the response immediately or escalates to a senior agent
7. Memory Update: The interaction is stored in a vector database for future RAG queries
8. Analytics: Ticket metadata is logged to a database for reporting

Each step is a visual node on the canvas. The entire workflow is inspectable, debuggable, and modifiable. No code required for the basic flow, but you can drop into JavaScript for custom transformations when needed.

This combination of visual simplicity and technical depth is what made n8n the go-to platform for AI workflow prototyping and production deployment.

The "Excel of AI" Vision

Jan Oberhauser articulated the transformation with a phrase that captured the ambition perfectly: n8n wanted to become the "Excel of AI."

The analogy was precise. Excel didn't invent spreadsheets, and it didn't require users to be programmers. But it gave billions of people a grid-based interface where they could organize data, write formulas, build models, and automate calculations. Excel became the universal tool for working with structured data.

Oberhauser envisioned n8n playing the same role for AI automation. Instead of a grid, you have a canvas. Instead of cells and formulas, you have nodes and connections. Instead of data transformations, you have AI model calls, tool invocations, and decision trees. The goal: a tool so fundamental and accessible that anyone can build AI-powered automations without writing code.

Critically, Oberhauser doesn't see AI replacing humans or code. He sees a trinity:

"The future is human plus code plus AI. Humans define the intent and make the decisions. Code handles the deterministic parts — the reliable, repeatable logic. AI handles the fuzzy parts — classification, generation, understanding context. n8n is the canvas where you orchestrate all three."

This "human + code + AI" framework explains why n8n's AI implementation feels different from competitors. Rather than bolting AI onto existing automation as a single action (Zapier's approach), n8n treats AI as a first-class citizen in a multi-step orchestration pipeline — where AI nodes sit alongside code nodes and human approval nodes on the same canvas.

The vision resonated with a massive and growing market. As companies raced to integrate AI into their operations, they discovered that the hard part wasn't the AI itself — it was the plumbing. Connecting an LLM to your CRM, your database, your email system, your Slack channels, and your business logic required exactly the kind of orchestration that n8n provided.

Revenue Explosion: From $7.2M to $40M ARR

The AI pivot didn't just change n8n's product — it transformed its business.

In 2024, n8n's annual recurring revenue (ARR) stood at approximately $7.2 million. By the end of 2025, that number had grown to an estimated $40 million — a staggering 5.5x year-over-year increase.

Oberhauser himself acknowledged the magnitude of the shift, stating that the AI pivot drove 4x revenue growth in just 8 months compared to what the company had achieved in the previous 6 years combined. Six years of steady, respectable growth as a workflow automation tool — blown away in less than a year by the AI wave.

The growth was fueled by several factors:

1. Developer virality: Tutorials on building AI agents with n8n flooded YouTube, Twitter, and Reddit
2. Enterprise adoption: Companies needed a way to orchestrate AI workflows, and n8n's self-hosting model addressed data sovereignty concerns
3. GitHub star explosion: n8n became the fastest-growing automation project on GitHub, creating a self-reinforcing awareness loop
4. Community nodes: The community contributed thousands of custom nodes, expanding n8n's integration surface far beyond what the core team could build

The revenue-per-employee metric tells an equally remarkable story. With just 67 employees, n8n generated approximately $597,000 in revenue per employee — an efficiency ratio that would make most SaaS companies envious, especially compared to competitors like Zapier with its roughly 800 employees.

The AI Automation Market Context

n8n's AI pivot didn't happen in a vacuum. By 2024-2025, the entire automation industry was being reshaped by AI:

• ChatGPT's launch (November 2022) made AI accessible to non-technical users, creating massive demand for AI-powered workflows
• LangChain's rise (late 2022-2023) provided a framework for building AI applications, but most developers still needed a way to deploy and connect them to real business tools
• Enterprise AI adoption accelerated as companies moved from AI experimentation to production deployments, requiring robust orchestration layers
• Agent frameworks emerged as the next paradigm after simple prompt-response interactions, with AI systems that could plan, use tools, and execute multi-step tasks

n8n was perfectly positioned at this intersection. It already had the visual workflow builder, the integration ecosystem, and the self-hosting model. Adding AI nodes was like giving a Swiss Army knife a new blade — the tool was already built for multi-step orchestration; AI was just the most powerful step it could now include.

The timing was almost eerily perfect. As one investor noted, n8n had spent five years building the "boring" infrastructure — execution engine, credential management, error handling, node ecosystem — that turned out to be exactly what AI automation required.

💰 Funding: From $1.5M Seed to $2.5B Unicorn

The Complete Funding Timeline

The most striking thing about this funding timeline is the velocity of the later rounds. n8n's valuation jumped from approximately $350 million to $2.5 billion in just four months — a 7x increase between the Series B (March 2025) and Series C (October 2025).

That kind of valuation acceleration is almost unheard of, and it reflects the market's conviction that AI automation is a generational platform shift, not an incremental product improvement.

The Investor Roster

The quality of n8n's investor base tells its own story:

• Sequoia Capital: The legendary Silicon Valley firm that backed Apple, Google, and Stripe — involved since the seed round
• Accel: Led the Series C; known for backing Facebook, Slack, and Atlassian
• NVIDIA (NVentures): The GPU giant's venture arm, a strategic bet on AI infrastructure
• Deutsche Telekom (T.Capital): Europe's largest telecom investing in AI automation
• Highland Europe: Led the Series B from their European growth fund
• Felicis Ventures: Led the Series A; early backers of Shopify and Twitch
• firstminute capital: Co-led the seed round alongside Sequoia

The combination of blue-chip Silicon Valley VCs, strategic corporate investors (NVIDIA, Deutsche Telekom), and European growth funds positions n8n as a truly global company with deep connections across the tech ecosystem.

⭐ The GitHub Stars Phenomenon

n8n's GitHub star trajectory is one of the most remarkable growth stories in open-source history.

In 2025 alone, n8n gained approximately 112,000 new GitHub stars, making it the #1 project in JavaScript Rising Stars for that year. To put this in perspective, that's more than most popular open-source projects accumulate over their entire lifetime.

The star growth wasn't organic curiosity alone — it was fueled by the AI automation wave. As developers discovered they could build complex AI agent workflows through n8n's visual interface, the project went viral on social media, YouTube, and developer communities. Every tutorial, demo, and blog post drove more stars, which drove more visibility, which drove more tutorials — a classic network effect.

By October 2025, n8n had surpassed 150,000 GitHub stars, placing it among the most-starred repositories on all of GitHub.

To put this in context, here's how n8n's star count compares to other well-known developer tools:

n8n is the most-starred workflow automation tool on GitHub by a wide margin. The star count alone doesn't determine a project's quality, but it does reflect the level of community interest, awareness, and engagement — all of which contribute to the ecosystem's health and growth.

🏢 Enterprise Adoption and Key Customers

Despite its developer-community origins — and the fact that it started as a single founder's side project — n8n has built remarkable enterprise traction:

• 3,000+ enterprise customers across industries
• 25% of Fortune 500 companies reportedly use n8n
• 230,000+ active users globally
• 400+ official integrations plus 5,834 community-contributed nodes

Notable Enterprise Wins

Vodafone UK deployed n8n for threat intelligence automation, saving an estimated £2.2 million in operational costs. The automation replaced manual processes for collecting, analyzing, and distributing threat intelligence data across security teams.

Delivery Hero, one of the world's largest food delivery platforms, used n8n to automate internal workflows, saving 200 hours per month — effectively freeing up more than one full-time employee's worth of labor.

n8n also established a partnership with Microsoft's Agent 365 ecosystem, integrating n8n's workflow automation capabilities into Microsoft's enterprise AI agent platform. This partnership is particularly significant because it positions n8n alongside Microsoft's own Power Automate offering — a testament to the unique capabilities n8n brings to AI workflow orchestration that even Microsoft's own tools don't fully replicate.

Ricardo Espinoza: From Community Contributor to First Hire

One of n8n's most compelling stories is that of Ricardo Espinoza, who contributed an extraordinary 60 community nodes to n8n's integration library. His prolific contributions caught the team's attention, and he was hired as n8n's first community-to-employee conversion — a powerful example of how open-source community engagement can create a pipeline for exceptional talent.

Espinoza's story embodies a pattern that repeats across the n8n ecosystem: passionate community members who build integrations for their own needs, share them publicly, and become evangelists for the platform. The community-contributed node library (5,834 nodes and counting) is arguably n8n's greatest competitive moat — no competitor comes close to this level of grassroots integration development.

The Community Ecosystem

n8n's community is one of its most underappreciated strengths. Beyond the raw GitHub star count, the ecosystem includes:

• 5,834 community-contributed nodes extending n8n's integration coverage far beyond the 400+ official nodes
• Active community forum with thousands of workflow templates, troubleshooting threads, and feature requests
• YouTube ecosystem: Dozens of independent creators producing n8n tutorials, driving organic discovery
• Template library: Pre-built workflows that users can import and customize, dramatically reducing time-to-value
• Discord and Slack communities: Real-time support channels where experienced users help newcomers

The Marketing Pivot: Removing the Lead Goal

One of Oberhauser's most counterintuitive decisions was how n8n approached marketing. In the "Building the Universal AI Automation Layer" interview, he revealed that n8n deliberately removed lead generation as a marketing KPI:

"We removed the lead goal from marketing entirely. Our marketing team's job is not to generate leads — it's to drive adoption. If people adopt n8n, the revenue follows. The moment you start optimizing for leads, you start creating gated content, you start annoying people, and you lose the community trust that's the actual growth engine."

Instead, n8n invested heavily in educational content — particularly YouTube. The strategy was simple: teach people how to build AI automations with n8n, and let the product sell itself. This created a content flywheel where n8n's own tutorials drove organic discovery, which attracted independent creators who made their own tutorials, which drove more GitHub stars, which drove more Google and YouTube search visibility.

The result was a marketing machine that grew by giving knowledge away rather than gating it — a model that would be validated by n8n's explosive growth when the AI wave hit.

The community dynamics create a virtuous cycle. More users lead to more community nodes, which attract more users, which generate more tutorials, which drive more GitHub stars, which increase visibility, which brings in more users. This flywheel effect is what propelled n8n from niche developer tool to mainstream AI automation platform.

🔐 Security: The Ni8mare Vulnerabilities

No discussion of n8n's history would be complete without addressing the critical security vulnerabilities discovered in early 2026.

Two severe CVEs (Common Vulnerabilities and Exposures) shook the n8n community:

A CVSS score of 10.0 is the maximum possible severity rating. Both vulnerabilities were classified as remote code execution (RCE) bugs, meaning attackers could execute arbitrary code on n8n servers.

CVE-2026-21858, nicknamed "Ni8mare" (a play on "nightmare" and "n8n"), was particularly alarming because it required no authentication — any n8n instance exposed to the internet was potentially vulnerable. Given that n8n workflows typically connect to sensitive systems (databases, email accounts, CRMs, payment processors) and store API credentials, the impact of exploitation could be catastrophic.

Both vulnerabilities were patched in version 1.121.0, and n8n's security team responded quickly once the issues were reported. But the incident highlighted a fundamental tension in the self-hosting model: when users control their own infrastructure, ensuring timely security patches across thousands of independent deployments is inherently more challenging than patching a centralized SaaS platform.

The Ni8mare vulnerabilities strengthened the case for n8n Cloud, where the n8n team manages patching and security updates automatically — a common dynamic in the open-source-to-cloud business model.

Lessons from Ni8mare

The security incident, while serious, also demonstrated the resilience of n8n's community. Security researchers responsibly disclosed the vulnerabilities. The n8n team issued patches quickly. Community members shared mitigation guidance in forums and Discord channels. And the incident sparked productive discussions about security best practices for self-hosted automation platforms.

Key takeaways from the Ni8mare incident include:

1. Never expose n8n directly to the internet without authentication and network-level protections (VPN, reverse proxy, IP allowlisting)
2. Keep n8n updated — patch management is critical for self-hosted deployments
3. Credential isolation — use environment variables and secret management tools rather than storing API keys directly in workflows
4. Network segmentation — run n8n in an isolated network segment to limit blast radius in case of compromise
5. Consider n8n Cloud for production workloads where security patching and monitoring are handled by the n8n team

🔄 n8n 2.0: Secure by Default (December 2025)

On December 5, 2025, n8n released version 2.0 — the platform's most significant update since the 1.0 production-ready milestone.

n8n 2.0 focused on three core themes:

Secure-by-Default Execution: In response to the growing importance of security (and perhaps foreshadowing the Ni8mare vulnerabilities), n8n 2.0 introduced stricter default security settings for workflow execution, reducing the attack surface for self-hosted instances.

Save vs. Publish Separation: n8n 2.0 introduced a clear distinction between saving a workflow (which stores your changes as a draft) and publishing it (which activates the workflow in production). This seemingly simple change addressed a major pain point — in previous versions, saving a workflow could inadvertently change the behavior of running production automations.

10x Faster SQLite Performance: For self-hosted instances using SQLite as their database backend, n8n 2.0 delivered a 10x performance improvement — a critical upgrade for users running n8n on smaller servers or edge devices.

The 2.0 release was also a statement of intent. It signaled that n8n was evolving from a developer tool into an enterprise platform with the stability, security, and governance features that large organizations require.

📊 n8n by the Numbers

Before comparing n8n to its competitors, let's look at the key metrics that define the platform as of early 2026:

These numbers paint a picture of a company that is punching well above its weight. With fewer than 70 employees, n8n serves a quarter of the Fortune 500, generates nearly $600K per head in revenue, and maintains a community ecosystem larger than most open-source projects dream of.

⚖️ n8n vs. Zapier vs. Make: The Automation Landscape

The workflow automation market has three dominant players, each targeting a different audience:

When to Choose n8n

n8n excels when you need:

• Self-hosted automation with full data control
• AI agent workflows with LangChain integration
• Complex, multi-step workflows with branching logic
• Custom integrations built from community nodes
• Cost predictability without per-task pricing

When to Choose Zapier

Zapier excels when you need:

• Quick, no-code automation for non-technical users
• The widest possible integration ecosystem (8,000+ apps)
• Simple trigger-action workflows
• Minimal setup and maintenance

When to Choose Make

Make excels when you need:

• Visual workflow design with complex routing
• A balance between power and usability
• Competitive pricing for medium-volume automations
• A growing integration library (2,500+ apps)

The Gap All Three Leave Open

Here's what none of these platforms do: they don't manage your projects, they don't build applications, and they don't give you an AI-native workspace where automation is integrated with task management, documents, and team collaboration.

That's where platforms like Taskade come in — combining AI agents, workflow automation, project management, and an app builder in a single workspace. More on that later.

The Automation Market in 2026: Where Things Stand

The workflow automation market is undergoing a seismic shift. What was once a niche category for connecting SaaS apps has become a central infrastructure layer for AI deployment:

• Total addressable market: The automation platform market is projected to exceed $30 billion by 2027, driven by AI integration and enterprise digital transformation
• AI automation is the growth driver: The fastest-growing segment of the market is AI workflow orchestration — building, deploying, and managing AI agent workflows
• Self-hosting is ascendant: Data sovereignty concerns, GDPR compliance, and the desire to control AI model access have made self-hosted automation increasingly attractive to enterprises
• Consolidation vs. specialization: Some players are consolidating (Zapier adding AI, n8n adding enterprise features) while new entrants specialize in AI-only automation (Relevance AI, Flowise)

n8n sits at a particularly interesting position in this landscape. It's too technical for Zapier's core SMB audience but too user-friendly for pure infrastructure buyers. This "developer-first, enterprise-ready" positioning — combined with the AI pivot — has carved out a large and defensible market segment.

🌍 The European IPO Ambition

In various interviews, Jan Oberhauser has expressed a clear ambition: he wants n8n to go public, and he wants to do it in Europe.

"I definitely want a European listing."

Jan Oberhauser, CEO of n8n

This is a significant statement in an industry where European tech companies almost universally choose to list on the NASDAQ or NYSE. Oberhauser's preference for a European IPO reflects both his pride in building a major tech company from Berlin and a desire to help build a stronger European tech ecosystem.

With a $2.5B valuation, $40M ARR growing at 5.5x year-over-year, and a clear AI automation narrative, n8n has all the ingredients for a successful public offering. The question is timing — and whether the market conditions and growth trajectory align for a 2026 or 2027 listing.

A European tech IPO of this magnitude would be a landmark event. While companies like Spotify and Adyen have listed in Europe, the vast majority of high-growth tech companies still default to US exchanges. An n8n IPO on the Frankfurt, Amsterdam, or London exchange could inspire other European founders to follow suit.

The European ambition is also strategic. n8n's headquarters in Berlin, its focus on data sovereignty through self-hosting, and its growing European enterprise customer base make it a natural champion for the European tech ecosystem. In a world where GDPR and the EU AI Act are shaping how companies deploy AI, a European-headquartered automation platform has inherent advantages.

🎙️ Jan Oberhauser: The Founder's Philosophy

Understanding n8n requires understanding its founder. Jan Oberhauser is not a typical Silicon Valley startup CEO. He doesn't come from a computer science background. He didn't drop out of Stanford. He didn't grow up dreaming of building a billion-dollar company.

He was a creative professional — a VFX artist who saw inefficiency, became an engineer who solved it, and then built a company to solve it at scale. This practical, problem-first approach permeates every aspect of n8n's design and culture.

In a Sequoia "Training Data" podcast appearance, Oberhauser spoke about the importance of keeping n8n accessible:

"The moment you make a tool that only engineers can use, you've already lost. The whole point is that the person who understands the business process should be able to automate it themselves."

This philosophy explains many of n8n's design decisions: the visual canvas interface (accessible), the JavaScript function nodes (powerful), the self-hosting option (no gatekeepers), and the fair-code license (transparent). Each choice reflects a bias toward empowering users rather than creating dependencies.

The Lean Machine: 140 Employees, $1B ARR Goal

Oberhauser's management style is similarly pragmatic. With approximately 140 employees as of late 2025, n8n is one of the leanest companies per dollar of revenue in all of SaaS. And Oberhauser intends to keep it that way:

"My goal is to reach $1 billion ARR with less than 500 employees. I think it's absolutely possible. With AI handling more and more of the development work, and with the leverage our platform model gives us, there's no reason to build a 5,000-person company."

The employee NPS tells its own story. In his Accel Spotlight On interview, Oberhauser revealed that n8n's internal employee NPS score sits between 95 and 100 — a number that most companies would consider impossible:

"When I tell investors our employee NPS is 95 to 100, they literally don't believe me. They think we're measuring it wrong. But it's real, and it comes from hiring the right people and giving them autonomy."

Hiring for Humility

Oberhauser's hiring philosophy is distinctive and deeply personal. He looks for what he calls "humble excellence" — people who are extraordinary at what they do but don't feel the need to broadcast it:

"I want people who are amazing but don't brag about it. The moment somebody walks into an interview and tells me how great they are, that's a red flag. I want people who are quietly brilliant, who let their work speak for itself."

This hiring filter creates a specific kind of culture — one where competence is assumed, ego is minimized, and collaboration happens naturally because nobody is jockeying for status. It's a philosophy that comes directly from Oberhauser's VFX background, where pipeline engineers worked behind the scenes to make other people's work possible.

The European Visibility Problem

One challenge Oberhauser has spoken about candidly is the visibility disadvantage of building from Europe rather than San Francisco:

"If you're a Silicon Valley company, you get 10x the press coverage, 10x the conference invitations, 10x the investor attention. European companies have to work much harder for the same visibility. That's changing, but it's still real."

Despite this, Oberhauser has leaned into the European identity rather than trying to import Silicon Valley culture. Berlin's engineering talent pool, lower cost of living, and proximity to European enterprise customers have been advantages that complement the company's capital-efficient approach.

The question is whether this lean approach can scale to meet the demands of a $2.5B company with enterprise customers, a growing community, and ambitions for a public listing. Oberhauser's $1B-with-500-employees target suggests he believes the answer is yes — that AI-augmented teams can accomplish what previously required armies of engineers and salespeople.

🎬 Inside the Founder's Mind: Jan Oberhauser Interviews

To understand where n8n is going, listen to its founder. These two interviews — one from the Series C announcement with Accel, one from a deep-dive on AI automation — reveal the thinking behind n8n's strategy, culture, and ambitions.

Accel Spotlight On: n8n's Jan Oberhauser

In this Series C announcement interview with Accel, Oberhauser discusses n8n's origin story in VFX, the "Excel of AI" vision, the 5.5x revenue growth, and why he wants to take n8n public on a European stock exchange:

Building the Universal AI Automation Layer

In this extended conversation, Oberhauser goes deeper on the AI pivot — the existential fear when ChatGPT launched, the Pinecone insight that reframed n8n's role in the AI value chain, the "human + code + AI" framework, and his goal of $1 billion ARR with fewer than 500 employees:

🔮 Quo Vadis, n8n?

n8n's journey from a VFX pipeline engineer's side project to a $2.5 billion AI automation platform took just six years. The speed of this transformation is remarkable — but perhaps even more remarkable is how precisely the company's inflection point can be traced to a single strategic decision: the AI pivot.

Before AI nodes, n8n was a solid workflow automation tool with a passionate developer community and steady growth. After AI nodes, n8n became the fastest-growing automation platform in the world, attracting Fortune 500 customers, billion-dollar valuations, and comparisons to the most transformative software platforms in history.

The challenges ahead are significant:

Competition: Zapier isn't standing still — it has been aggressively adding AI features. Make is growing rapidly. And a new wave of AI-native automation tools (Relevance AI, Activepieces, Windmill) is entering the market. Microsoft Power Automate has vast enterprise distribution.

Security: The Ni8mare vulnerabilities demonstrated the risks inherent in self-hosted automation platforms. As n8n pushes into enterprise, security hardening and rapid patch distribution become critical.

Monetization: With 150,000+ GitHub stars but only $40M ARR, n8n's conversion from free self-hosted users to paid cloud customers remains a work in progress. The gap between community adoption and revenue capture is the defining challenge of every open-source business model.

Scaling the Team: At 67 employees, n8n is remarkably efficient. But building an enterprise-grade platform, supporting thousands of customers, and maintaining a massive open-source community will require significant headcount growth — without losing the engineering culture that got them here.

The "Excel of AI" Bet: Oberhauser's vision is audacious. Excel became universal because spreadsheets solve a universal problem. Whether AI automation reaches that level of ubiquity — and whether n8n is the tool that captures it — remains to be seen.

Regulatory Landscape: The EU AI Act introduces new compliance requirements for AI systems. As an EU-headquartered company, n8n has both the challenge and opportunity to build compliance features into its AI automation platform. Companies deploying AI agents through n8n will need audit trails, explainability, and governance — features that could become a competitive advantage if n8n builds them first.

Platform Risk: n8n's AI capabilities depend on third-party model providers (OpenAI, Anthropic, Google). If those providers change their APIs, pricing, or terms of service, n8n's AI workflows could break. This platform dependency is manageable but creates ongoing risk that self-hosted users need to consider.

One thing is clear: the automation landscape has been permanently transformed by AI, and n8n is at the center of that transformation. Whether through an IPO, continued growth, or strategic partnerships, Jan Oberhauser's bet that smart people shouldn't depend on engineers for automation is paying off in ways he likely never imagined when he was automating VFX pipelines in a Stuttgart studio.

The VFX pipeline engineer from Stuttgart who wanted to help smart people automate their own work has built a platform that's doing exactly that — at a scale he probably never imagined. And the most remarkable part? If n8n truly becomes the "Excel of AI," the story is still in its earliest chapters.

🐑 Before you go... n8n automates workflows, but it can't manage your projects, build applications, or give you an AI-native workspace. Taskade combines everything in one platform.

• 🤖 AI Agents: Build custom AI agents with persistent memory, 22+ built-in tools, and multi-model support from OpenAI, Anthropic, and Google. Unlike n8n's automation-only agents, Taskade agents live inside your workspace and collaborate with your team.

• 🔄 Workflow Automation: Automate tasks and projects with Temporal durable execution, branching, looping, and filtering — no separate automation tool needed.

• 🧬 Genesis App Builder: Describe what you need, Taskade builds it. Create complete AI-powered applications with a single prompt — it's vibe coding for productivity apps.

• 💬 AI Chat: Got a question about your project? The AI Chat gives you answers and helps your team stay on the same page.

• ✏️ AI Assistant: Brainstorm ideas, generate content, organize tasks, and ensure you always know what to do next.

n8n users looking for a complete workspace should also check out our n8n alternatives guide, Zapier history article, and free n8n alternative comparison.

Want to give Taskade a try? Create a free account and start today! 👈

🔗 Resources

1. https://n8n.io/
2. https://github.com/n8n-io/n8n
3. https://github.com/n8n-io/n8n/issues/40
4. https://blog.n8n.io/n8n-2-0/
5. https://www.youtube.com/watch?v=y4jQ5VqR02M
6. https://faircode.io/
7. https://docs.n8n.io/hosting/
8. https://n8n.io/pricing/
9. https://www.accel.com/noteworthy/accel-invests-in-n8n
10. https://techcrunch.com/2025/10/n8n-series-c-2-5-billion/

💬 Frequently Asked Questions About n8n