Iceland-based Euler has raised a €2 million seed round co-led by Frumtak Ventures and Kvanted to scale its AI-powered 3D printing software that detects and prevents print defects in real time. A spinout from the Technical University of Denmark, Euler uses deep AI to enhance reliability in laser powder bed fusion and selective laser sintering — helping industrial manufacturers avoid costly failures and ensure consistent production quality. The fresh funding will accelerate team expansion, particularly in sales and marketing, and drive product development and international rollout following a successful pilot and upcoming Formnext debut in Frankfurt. Frumtak Ventures Partner Ásthildur Otharsdóttir and Kvanted Partner Eerik Paasikivi join the Euler board.
Euler is an Icelandic deep-tech company developing AI-powered software to improve the reliability of industrial 3D printing. Originating as a spinout from the Technical University of Denmark, the company focuses on real-time defect detection and process monitoring for laser powder bed fusion and selective laser sintering systems. By analyzing camera data and machine signals with deep learning models, Euler helps manufacturers prevent print failures, reduce waste, and ensure quality consistency without expensive hardware upgrades. Its technology integrates with existing 3D printers and serves clients across aerospace, healthcare, and advanced manufacturing sectors.
Euler is announcing this round in advance of its appearance at Formnext in Frankfurt, Germany (18-21 November 2025), an annual tradeshow and conference for additive manufacturing (AM) and industrial 3D printing. During Formnext, Euler will officially launch its product and open up for company sign-ups, following a successful invite-only paid pilot programme, as well as announcing official partnerships with Autodesk and Scanlab.
Euler will use this investment – from some of the Nordic region’s major VCs – to accelerate the rollout of its platform, expand its team (with a focus on its sales and marketing departments), and scale product development. This round follows an initial €2mn raised in public European grants since the company’s founding. Additionally, Euler has begun the process of trademarking its core technology, having already applied for three separate patents.
Euler’s emergence reflects an overdue maturation of 3D printing as a viable large-scale industrial process. In September 2025, LEGO announced the first use of mass-produced 3D printed components for its sets, with Apple announcing the use of 3D printed metal components for its most recent model, the iPhone Air (having already used 3D printed parts for its Apple Watches since 2024).
Valued at $20+ billion, the global 3D printing industry has long promised to transform production by enabling the creation of lighter and more complex components, while reducing material waste, production emissions, and serving as a valuable enhancement to traditional manufacturing technologies.
However, despite optimistic predictions, large-scale adoption of 3D printing has been limited by the difficulty of ensuring components meet strict safety and performance standards – especially when producing parts for highly regulated industries such as aerospace or defence. Small disruptions have resulted in print failures, and without real-time supervision, defects are often discovered only after production, leading to costly rework or scrapped parts.
Euler’s platform revolutionises this process by providing sophisticated automated real-time monitoring, alerting manufacturers to potential defects before they occur, saving crucial time and resources, leading to more reliable part production at scale. In a whitepaper conducted with the Danish Technological Institute, Euler demonstrated a 77% reduction in time spent on failed builds, translating to potential savings of $115k in operating costs and more than 20% increase in revenue through improved overall equipment effectiveness.
Autodesk Director of Additive Manufacturing, Alexander Oster comments “In my 25 years of being in this industry, I have very rarely seen a team and product which so profoundly leapfrogs the state of the art in the way Euler does”
The Technical University of Denmark spinout leverages deep AI and process expertise to enhance fault detection for laser powder bed fusion (LPBF) and selective laser sintering (SLS) 3D printing. Euler can be easily integrated with market-leading 3D printers, and leverages printer camera data and AI algorithms to conduct 3D printing analysis without expensive monitoring equipment. Euler already serves several high-profile international clients including the UK’s fastest growing additive manufacturing startup, Alloyed, Dutch manufacturing company KMWE which delivers innovative machining, assembly and additive solutions across aerospace, semiconductor, healthtech and industrial markets, and with innovative RTOs such as the Danish Technological Institute and the Korea Institute of Industrial Technology.
Euler co-founder and CEO Dr Eyþór Rúnar Eiríksson: “Additive manufacturing has yet to live up to its hype, despite its disruptive potential. Challenges around cost, scalability, and quality assurance remain. Euler is already helping manufacturers overcome these issues, and this investment will enable us to continue our growth and expand exponentially, solidifying additive manufacturing as a reliable production process.
Frumtak Ventures Partner Ásthildur Otharsdóttir: “This investment is representative of the next wave of innovative Icelandic startups, combining academic nuance with advanced technology to solve a long-standing industry issue. Their progress reflects the growing maturity of the Nordic startup ecosystem and its ability to compete globally.”
Kvanted Partner Eerik Paasikivi: “Additive manufacturing is entering a new era of industrial adoption, and Euler’s platform is at the forefront of this. Their technology is bringing the reliability and intelligence needed to finally make large-scale 3D printing viable.”
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Read the orginal article: https://arcticstartup.com/euler-raises-e2m-seed/
