CARLO is a surgical robot designed by Swiss company Advanced Osteotomy Tools (AOT). It uses a revolutionary non-contact cold laser ablation procedure to cut and reshape bone in osteotomy surgery. This pioneering technique reduces the surgical workload, cuts the risk of infection, and makes possible new approaches to treatment, including the use of implants. AOT seeks FDA approval & 'eyes' for its robot For the technique to succeed, AOT needed to teach its robo surgeon CARLO to 'see'. What's more, the firm wanted to gain FDA approval to market its device in the US. As such, the business required a partner that could combine strategy and regulatory experience with deep domain expertise and extensive capabilities in data engineering, machine learning, and software engineering. Zühlke was the natural choice. Together, our teams and AOT developed a medical machine learning process. Building on this, we implemented and validated a legally compliant data platform for data collection and developing medical machine learning models. Lastly, the team implemented an initial image recognition application, for which the new platform proved invaluable. This initial proof of concept involved enabling the robot to use optical coherence tomography to orient itself and precisely locate the bone and cutting sites – in other words, giving the surgical robot 'eyes'. Pioneering data platform lays the foundations for growth & innovation With our help, AOT secured a major milestone on the path towards commercialisation. The legally compliant data platform we developed paved the way for FDA approval and enabled the business to rapidly develop further medical software applications for a wide range of applications. In giving 'sight' to its pioneering robo surgeon, we demonstrated how the device could transform osteotomy and therapies, improving outcomes for AOT and patients alike. Explore our MedTech & healthcare expertise Contact person for Switzerland Dr. Gabriel Krummenacher Head of Data Science Gabriel Krummenacher leads the Data Science Team at Zühlke and has several years of experience in conducting data analytics and machine learning projects. His main focus is on medical machine learning applications and bringing prototypes to production. He holds a PhD and M.Sc. from the Institute for Machine Learning at ETH, where he worked on scalable methods for large-scale and robust learning, wheel defect detection and sleep stage prediction with deep learning. Contact gabriel.krummenacher@zuehlke.com +41 43 216 64 56 Your message to us You must have JavaScript enabled to use this form. First Name Surname Email Phone Message Send message Leave this field blank Your message to us Thank you for your message. Our work Medical Device and Healthcare Biorithm pioneers next-generation maternity care with remote monitoring technology Learn more Banking, Commerce and Consumer Goods Zühlke's GenAI Project Finder boosts presales efficiency Learn more Medical Device and Healthcare Berlinger pioneers smarter medication shipments with IoT Learn more Go to case studies Deliver transformative impact with Zühlke. Speak to our team today. Get in touch