Team: Louis-Alexandre Etezad-Heydari, Grossman School of Medicine, PhD.; Jonathan Brown
About the Venture: We are an AI platform for imaging diagnostics that enables every clinical expert to train advanced AI models without the need for AI expertise. Our goal is to build the world’s first AI model repository and marketplace for medical AI models.
A: AI point solutions fundamentally fail to transform healthcare for two critical reasons:
First, they create an impossible economic choice for hospitals: either invest millions to implement narrow AI solutions that each cover less than 0.1% of 1,000+ known diseases, or wait years for new solutions while managing an ever-growing maze of vendors and systems.
Second, these rigid solutions ignore the reality of clinical practice. Every hospital and physician group has developed unique diagnostic and treatment workflows over years of experience. Point solutions force doctors to abandon their proven approaches to accommodate inflexible AI systems, resulting in poor adoption and minimal clinical impact.
éo transforms this paradigm by putting AI development directly in clinicians’ hands. Our visual intelligence platform enables healthcare professionals to create custom AI solutions that perfectly match their clinical workflows—no technical expertise required. Instead of adapting to rigid point solutions, doctors can now build AI tools that adapt to them.
Through our marketplace, clinicians can collaborate with peers, share their innovations, and monetize their expertise, creating a sustainable ecosystem of physician-driven AI development that scales across healthcare.
A: Our team combines deep expertise in AI, cybersecurity, engineering, as well as mathematical modeling. Louis-Alexandre, a second-time founder, developed a breakthrough image-agnostic AI framework for computer vision for content moderation. He connected with our CTO Kim Nilsson, who gained global recognition for solving a $300M cryptocurrency heist through advanced data analysis.
Louis-Alexandre and I have been friends for 10 years. When he needed help industrializing his AI framework for monetization, my background as a mathematician and 15+ years in risk modeling with expertise in analyzing complex data patterns to predict outcomes in high-stakes environments—made me the perfect fit. While helping scale his AI framework, I had a key insight: healthcare’s AI adoption challenge isn’t fundamentally a medical problem—it’s a data problem. This is a perfect opportunity to take the capabilities out of big tech and into the hands of the people who are making a difference: doctors.
Our complementary backgrounds perfectly align to democratize AI development: Louis-Alexandre’s AI framework, Kim’s expertise in data-privacy and securing sensitive data, and my experience in making complex data actionable.
A: We’re not building another point solution—we’re creating an entirely new category that democratizes healthcare AI development.
Current Approach:
Our Innovation:
Unique Advantage: Our co-founder previously attempted this vision in 2014, but the technology wasn’t ready. His startup was acquired by Twitter, and now he brings crucial insights to make this vision reality at the perfect technological moment.
A: Our co-founder Louis-Alexandre’s deep connection with NYU, where he completed his PhD in Neuroscience and met his first startup co-founder, initially drew us to the NYU Entrepreneurs Challenge. His firsthand experience showed us how NYU fosters innovation through its vibrant entrepreneurial community and extensive healthcare network. We’re excited to tap into NYU’s unique ecosystem of clinicians, researchers, and mentors who can provide valuable insights as we transform how AI is developed in healthcare. The Challenge’s structured approach to venture development and its track record of launching successful healthcare startups makes it an ideal platform for accelerating our growth.
A: Our pivotal moment came through our partnership with a biotech company. While we initially envisioned a vertical-agnostic platform, this collaboration revealed healthcare’s urgent need for democratized AI development. It sparked a critical strategic shift: rather than trying to serve everyone, we narrowed our focus exclusively to healthcare. This decision transformed our development approach, allowing us to deeply understand clinicians’ unique needs and build specifically for their workflows. The clarity from this pivot helped us create a more focused product roadmap, identify our ideal customer profile, and develop a repeatable solution that truly resonates with healthcare professionals. What started as a single partnership became the catalyst for our entire strategic direction.
A: Our biggest challenge has been accessing key decision-makers within healthcare institutions. To overcome this, we’ve leveraged our network of supporters who believe in our vision. Their warm introductions have significantly accelerated our path to first meetings with stakeholders. This relationship-based approach has not only shortened our sales cycle but led to more meaningful conversations since we come pre-validated by trusted sources.
A: We’ve achieved a significant milestone by securing commercial pilot agreements with major healthcare institutions who recognize our innovative approach. These partnerships validate our vision for democratizing AI development in healthcare. Our next critical milestone is converting these pilots into revenue-generating relationships. The pilot discussions have already provided valuable insights into how we can deliver maximum value to these institutions.
A: AI is fundamentally rewriting the rules of entrepreneurship. My key advice: invest time learning AI tools that can compress days of work into hours. Tasks that previously required multiple hires can now be handled by one person with the right AI stack. When building your team, focus only on members who bring unique value that AI can’t replicate. This approach has allowed us to stay lean while moving quickly and allocate resources to truly strategic hires.
