MedAI: clarity for relatives and doctors in the toughest times

Eight ambitious AI startups have been selected to compete in the AI Pitch Competition. The finals are on November 13, 2025, and IO+ will portray each contestant in the run-up to that event. The AI Pitch Competition is a Brabant-based contest that highlights the most innovative AI solutions, offering startups the opportunity to present their ideas, connect with industry leaders, and accelerate their growth. Today, we show what MedAI has in store for the world. Co-founder Paul Söntgerath answers our questions.

What specific AI technology is at the core of your solution?

"When a patient enters a coma after a cardiac arrest, it often takes more than a day before doctors can indicate whether recovery is likely. During this waiting period, families live in painful uncertainty, and caring for comatose patients requires intensive time and attention from hospital staff. At MedAI, we develop an AI model that analyzes brain activity via EEG to provide earlier indications of outcome - often within just a few hours rather than days. This means doctors receive timely support in their assessments, families gain faster clarity, and intensive care units can operate more efficiently.

Our technology builds on deep learning, using convolutional neural networks trained on thousands of hours of EEG data. While other research focuses on maximizing prediction accuracy, MedAI is the only one prioritizing the early availability of reliable outcome indication, bridging a crucial gap between clinical urgency and diagnostic precision."

How scalable is your AI solution?

"Our solution is designed to be highly scalable because it builds on EEG data that is already routinely collected in intensive care units worldwide. We aim to integrate our software directly with existing EEG equipment, enabling hospitals to adopt it without major workflow changes. One main challenge lies in regulation. Bringing a medical AI solution to clinical practice requires navigating complex legal frameworks and obtaining the necessary medical certifications.

Despite these challenges, we see regulation as an essential part of responsible innovation. By designing for compliance and patient safety from the very beginning, we are building a strong foundation that will allow MedAI to scale safely and confidently across borders."

How does your startup address potential ethical concerns related to bias, fairness, or transparency in AI decision-making?

"Ethical responsibility is central to how we develop our technology. To minimize bias, our models are trained on EEG data from hospitals across Europe and the United States, ensuring diversity in both patient populations and clinical settings. In the coming stages, we aim to expand this to include datasets from other parts of the world, so our AI system learns from a broader, more representative range of patients.

Transparency is equally important. Our tool is designed to support, not replace, medical decision-making, and we aim to make predictions interpretable so doctors can understand and trust the outcome indications. By combining diverse data with clinical oversight, we ensure that MedAI’s technology remains fair, explainable, and aligned with real-world medical practice."

In what ways do you believe your AI solution can positively impact society?

"We believe MedAI can make a meaningful difference for both families and healthcare professionals. By providing earlier outcome indications for comatose patients after cardiac arrest, our technology helps families receive clarity sooner during one of the most difficult moments in their lives. For hospitals, it supports more efficient use of intensive care resources and helps doctors make faster, data-driven decisions when time is critical. We are aware that introducing AI into healthcare also brings responsibility. One possible risk is that clinicians might rely too heavily on automated predictions. To prevent this, our tool is designed to support, not replace, medical judgment, and its output is always intended to be interpreted alongside clinical expertise."

Tell us more about your entrepreneurial journey

"One of our biggest hurdles has been obtaining high-quality EEG data to train and validate our models. Medical data is often sensitive and tightly regulated, which makes it difficult for startups to access. We overcame this by building collaborations with hospitals and combining anonymized clinical data with large, open-source datasets, providing a strong foundation for development and testing.

At the same time, the growing interest in AI within healthcare has worked in our favor. Many medical institutions are eager to explore how AI can support clinical decision-making, and there is increasing public and governmental investment in responsible AI innovation. This environment motivates us to grow through collaboration: building technology that aligns with real clinical needs and contributes to the broader digital transformation of healthcare."

How are you preparing for the growing regulatory frameworks around AI, such as the GDPR, the AI Act, and other data privacy laws?

"We are still in the early stages of preparing for medical certification and regulatory compliance, but we are very aware of its importance. Although we are not yet in the formal compliance phase, we keep regulation in mind from the start by focusing on data security, transparency, and traceability in our development. As we move toward clinical validation, these early considerations will help us navigate the necessary approval processes efficiently and responsibly."

Future vision: What is your long-term vision for your AI solution?

"In the long term, we want to bring MedAI from research to real-world clinical practice and make it accessible to intensive care units worldwide. Our vision is to establish early neurological prognosis as a new standard of care after cardiac arrest, where artificial intelligence supports doctors in providing timely and data-driven insights. Beyond that, we see potential to expand our technology to other neurological conditions that rely on brain monitoring, such as stroke or traumatic brain injury. Over the next decade, we aim for MedAI to help shape a future in which AI becomes a trusted part of healthcare, improving decision-making, efficiency, and patient outcomes."

What opportunities does your location give you? What is still missing in the ecosystem you are part of?

"Being located in the Netherlands, and especially in Brabant, gives us a unique advantage. The region combines a strong medical network with a vibrant technology and innovation ecosystem. Eindhoven, at the heart of the Brainport region, connects academia, hospitals, and startups in a way that makes collaboration and knowledge exchange both easy and natural. There is also growing national and European support for responsible AI development, creating many opportunities for partnerships and funding. What we still see missing is a smoother pathway for early-stage medical AI startups to access clinical data and pilot opportunities. Bridging that gap would help innovations like ours move faster from the lab to real patient care, something we hope to contribute to as MedAI grows."

The AI Pitch Competition: Why will you win this contest?

"We believe we will win because MedAI addresses a problem that truly matters. Every year, thousands of families face the uncertainty of not knowing whether their loved one will recover from a coma after cardiac arrest. Our technology aims to give them clarity sooner, while helping doctors make faster and more data-driven decisions. What makes us stand out is that we are not just building another AI model. We are developing a clinically grounded solution with hospitals, focused on a clear, urgent medical need. Our team combines technical expertise with a strong sense of purpose, and we are driven by the belief that artificial intelligence should serve humanity where it matters most: in healthcare and in moments of life-defining impact."