Dutch AI Startup Secures €2.3 Million to Prevent Post-Surgery Infections Using Machine Learning
Netherlands, Saturday, 31 January 2026.
Amsterdam-based Healthplus.ai has raised €2.3 million to expand its PERISCOPE® system, which uses artificial intelligence to predict individual patients’ infection risks after surgery and provides targeted recommendations to medical teams. The platform can save hospitals up to €4 million annually by reducing costly post-operative complications and integrates seamlessly with existing electronic health record systems across European hospitals.
HealthTech Innovation Category and Technology Fundamentals
This development falls squarely within the healthtech sector, specifically focusing on medical technology applications of artificial intelligence [GPT]. Healthplus.ai’s PERISCOPE® system represents a sophisticated approach to perioperative care, utilizing machine learning algorithms to analyze patient data and predict infection risks following surgical procedures [1]. The technology addresses a critical healthcare challenge: post-operative infections remain one of the most significant sources of complications, extended hospital stays, and increased costs in modern healthcare systems [GPT]. By leveraging predictive analytics, the platform aims to shift medical care from reactive treatment to proactive prevention, allowing healthcare teams to implement targeted interventions before complications arise [1].
How PERISCOPE® Works and Its Clinical Benefits
The PERISCOPE® system operates by integrating directly with existing electronic patient record (EPD) systems commonly used across Dutch and broader European markets, including Epic, Oracle Cerner, and ChipSoft [1]. The platform automatically calibrates its predictions to work accurately across different types of hospitals while maintaining compliance with all applicable regulations [1]. When analyzing patient data, the system generates patient-specific risk assessments for post-operative infections and directly links these predictions to actionable recommendations for clinical teams [1]. This approach enables healthcare professionals to implement preventive measures tailored to individual patient risk profiles, potentially reducing both the incidence of complications and the associated workload on medical staff [1]. The technology’s seamless integration capabilities ensure that adoption can occur without disrupting existing hospital workflows or requiring extensive system overhauls [1].
Financial Impact and Market Expansion Strategy
The financial implications of PERISCOPE® are substantial, with the system capable of saving hospitals up to €4 million annually by reducing costly post-operative complications [1]. This significant cost reduction potential stems from decreased readmission rates, shorter hospital stays, and reduced need for additional treatments when infections are prevented rather than treated after occurrence [GPT]. The funding round, completed on January 18, 2026, was led by Elevating Capital and LUMO Labs, with additional participation from Pathena Venture Capital, Leistone (Renza Family), and ROM InWest [1][2]. Healthplus.ai plans to deploy this €2.3 million investment to accelerate expansion across Europe and initiate operations in the United States market [1]. The company also intends to further develop its AI risk models to cover all phases of the surgical process, potentially expanding beyond post-operative infection prediction [1].
Leadership and Regional Innovation Ecosystem
Dr. Bart Geerts, CEO and founder of Healthplus.ai, emphasized the company’s commitment to integrating clinically validated, regulatory-approved AI into daily hospital practice through close collaboration with surgical specialists, nurses, and IT teams [1]. The Amsterdam-based company exemplifies the innovation capabilities of North Holland’s life sciences and health ecosystem, which combines world-class AI expertise with clinical innovation in healthcare [1]. Sara Schaafsma, Investment Manager at ROM InWest, highlighted that the technology enables doctors and nurses to create better treatment plans through accurate patient stratification, allowing for faster intervention with high-risk patients while enabling low-risk patients to return home safely sooner [1]. This approach not only helps patients recover more quickly but also makes specialist work more efficient and reduces strain on the healthcare system [1]. ROM InWest’s involvement demonstrates how regional capital and networks are supporting AI innovations that improve patient outcomes while strengthening the life sciences and health ecosystem in the Amsterdam region [2].