Euler has launched an intelligent process monitoring platform designed to make industrial 3D printing predictable at scale. The company is pairing the debut with a €2 million seed round co-led by Frumtak Ventures and Kvanted. Its stated mission is to eliminate part variability and failed prints by analyzing images manufacturers already collect.
Market Context
Industrial 3D printing has long promised lighter, more complex parts with reduced material waste and emissions. Adoption at scale has lagged because reliability and certification hurdles are tough in sectors such as aerospace and defense. Failures detected after production can trigger costly rework or scrap, which erodes the business case for additive manufacturing.
Technology and Product
Euler’s software provides automated, real-time monitoring that flags potential defects before they occur. The platform integrates with leading 3D printers and processes data from built-in cameras using AI, so no additional sensors are required. It supports laser powder bed fusion and selective laser sintering, aiming to improve fault detection and production consistency.
Funding and Governance
The €2 million seed financing is co-led by Iceland’s Frumtak Ventures and Nordic industrial tech investor Kvanted. Frumtak Ventures Partner Ásthildur Otharsdóttir and Kvanted Partner Eerik Paasikivi are joining Euler’s board. The company plans to use the capital to accelerate platform rollout, grow its team, and advance product development.
Early Traction and Results
Customers include Alloyed in additive manufacturing, KMWE across aerospace, semiconductor, healthtech, and industrial markets, and research organizations such as the Danish Technological Institute and the Korea Institute of Industrial Technology. In collaboration with the Danish Technological Institute, Euler reported a 77 percent reduction in time spent on failed builds. The same work indicated more than a 20 percent revenue uplift tied to improved overall equipment effectiveness.
Origins and Differentiation
A spinout of the Technical University of Denmark, Euler blends process expertise with deep AI to target the root causes of print variability. By leveraging existing camera data rather than proprietary hardware, the platform lowers deployment cost and complexity. Real-time insights and proactive alerts are intended to bring predictability to high-value, tightly regulated environments.
Strategy and Next Steps
Euler is rolling out its software to more production sites while investing in features that expand cross-printer compatibility and analytics depth. The company has begun protecting core technology with trademark applications and three patent filings. Management believes these steps will help standardize quality workflows and reduce the gap between pilot projects and full-scale additive production.
Industry Implications
If reliability barriers fall, manufacturers could shift more parts from subtractive or cast methods to additive processes. That shift could compress lead times, reduce inventory risk, and support lighter designs that improve performance. Gains in first-time-right printing also align with sustainability goals through reduced scrap and energy use.
Customer Value Proposition
For operators, early defect detection helps avoid cascading failures that waste build time and materials. For quality teams, continuous monitoring creates traceability that supports audits and certification. For executives, higher equipment effectiveness and yield can improve margins and strengthen the case for scaling additive programs.
Euler’s launch and seed round position the startup to address one of industrial 3D printing’s most persistent bottlenecks, consistent part quality. The combination of camera-based monitoring, AI-driven analysis, and hardware-agnostic integration targets the practical realities of factory floors. With new capital, board oversight, and early performance data, the company is moving to translate pilots into production-level reliability.