The company’s Series C round, which included participation from Nvidia’s investment arm, values n8n at $2.5 billion, according to a Thursday (Oct. 9) announcement. Based in Germany, n8n helps companies develop and deploy agentic AI automations.
“n8n has built the automation and orchestration layer for the AI era: today, more than 80% of workflows built on n8n embed AI agents,” Accel, which led the funding round, wrote in its own announcement. “n8n has dramatically expanded the share of work that can be automated. Teams can fully customize workflows, mixing AI agents with deterministic steps and team inputs where required.”
Launched in 2019, n8n began as an automation tool, then became a platform for AI orchestration and cross-team collaboration, the company said in its announcement.
In an interview with Bloomberg News, n8n CEO Jan Oberhauser said his company’s tech has let customers such as Vodafone make significant cost cuts.
“We’ve seen billions of dollars going into AI investment, but many organizations aren’t seeing meaningful results,” he said. “We’re saving users millions of dollars.”
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Oberhauser said the company’s revenues have risen by tenfold in the past year but he declined to reveal an exact figure.
The company’s funding round is happening at a moment where “agentic commerce has overtaken Gen AI as the focus” of the AI world, as PYMNTS wrote last week.
“As CFOs plan for 2026, the real question is not whether to spend on GenAI, enterprise AI, or agentic AI but how these tools solve the problems that keep them up at night,” Kevin Akeroyd, chief executive of Sovos, said in an interview with PYMNTS.
“They’re weighing how AI can improve efficiency in areas such as tax compliance and reporting, while reducing risk as regulations evolve. The best budgets balance ambition with caution, leaving room to test new technologies while doubling down on proven enterprise applications.”
Research by PYMNTS Intelligence has found that 26.7% of chief financial officers (CFOs) plan to raise generative AI budgets in the next 12 months, compared to 53.3% a year ago.
This decline, the same report said, “highlights a pivot from experimental adoption to more disciplined deployment.”
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