If you look at healthcare as a system, it can be segmented by the logic of how events unfold. Broadly speaking, there are three major blocks: Prevention, Early Detection, and Diagnosis & Treatment. All three matter deeply, but if the goal is to move the system forward — not in theory, but in practice — then Early Detection is where the real leverage lies.
The first segment is Prevention. It’s about stopping diseases before they happen or dramatically reducing the risks of them developing. True prevention is vaccination, lifestyle change, nutrition, physical activity, stress management, early metabolic and behavioral interventions. It’s absolutely critical and, in the long term, will define the future of health. But there’s a catch: prevention requires people to change habits, commit over long periods of time, and engage deeply in their own behavior. It’s a slow, human process that’s hard to automate. That’s why, even though it’s vital, Prevention is the hardest place to start — especially if your goal is to build scalable technology.
The third segment is Diagnosis & Treatment. This is where diseases are diagnosed, managed, and treated. We’ve spent years here, working on cancer diagnostics. It’s a massive field with endless opportunities for improvement — faster, more accurate, more accessible care. But it’s also a space full of friction: complex regulation, long adoption cycles, conservative protocols, and systemic inertia. You can optimize it, but changing the core logic from inside that segment is nearly impossible.
And then there’s the space in between — the one most people overlook: Early Detection. This is the sweet spot between prevention and treatment, and we believe it’s the most powerful lever for real transformation. Here, technology can deliver the highest clinical and economic impact with the least resistance from the system.
Take melanoma as an example: if it’s detected at stage I, survival is around 99%. By stage III, it drops to about 50%. That’s not just a statistic — it’s the difference between a minor outpatient procedure and years of chemotherapy, disability, and massive healthcare costs. Or cervical cancer: early detection can stop the disease before it becomes invasive. The same applies to diabetes, hypertension, heart failure — catching them early means managing risks instead of fighting consequences.
From an economic standpoint, early detection is one of the most underestimated opportunities in healthcare. According to WHO, every $1 invested in early diagnostics returns $7–10 by reducing treatment costs and productivity losses. And that doesn’t even account for the impact on quality of life, longevity, and workforce participation.
Technology fits this space perfectly. Machine learning, real-world data analysis, voice and text interfaces, LLMs capable of integrating behavioral, clinical, and contextual signals — all of it makes it possible to create a new layer of proactive monitoring that delivers clinical impact without clinical infrastructure. We don’t need to rebuild hospitals — we just need to add an intelligent layer on top of what already exists.
That’s why we chose Early Detection as our starting point. It’s the place where technology can truly change lives — and the economics of healthcare itself. It’s the bridge between reactive and proactive medicine. And, honestly, it’s the best possible entry point into a new era — an era where medicine doesn’t wait for illness, but predicts it.
