Why I’m Investing in SkinBit: The Future of AI-Driven Skin Cancer Care

A Vision of Decentralized Preventive Care

I believe healthcare’s future lies in decentralized, walk-in pods—neighborhood access points where preventative screening is fast, affordable, and universally accessible. SkinBit is an early real‑world realization of this vision in dermatology: an AI-powered, full-body skin scanner built specifically for early skin cancer detection. It’s a tangible, working glimpse into what widespread preventative medicine will soon look like.

The Skin Cancer Crisis — In Numbers

Skin cancer is the most common cancer in the U.S., with more new cases annually than all other cancers combined, according to the American Cancer Society. About 1 in 5 Americans will develop it by age 70.

Daily, nearly 10,000 people are diagnosed, and more than two people die every hour. Melanoma accounts for roughly 5% of skin cancer cases but causes the majority of deaths. Survival rates exceed 99% when detected early, but decline steeply once it spreads. Non‑melanoma skin cancers (basal cell and squamous cell carcinomas) make up millions of additional cases each year, straining screening systems already facing workforce shortages.

SkinBit’s AI‑Powered Solution

SkinBit’s “Sentinel” scanner delivers a complete full-body skin scan in under 60 seconds. Using high-resolution imaging and AI, the system flags lesions with greater accuracy than typical human exams. All flagged results are reviewed by board-certified dermatologists before being shared with patients. Each scan is stored as a digital baseline, enabling longitudinal tracking of changes in size, shape, or color over time. By turning periodic skin exams into continuous, data-informed monitoring, SkinBit delivers a fundamentally different level of proactive healthcare.

The Founding Team — Why They Matter

What especially convinced me to invest in SkinBit was its founding team—a compelling blend of personal experience, clinical acumen, technical excellence, and product execution skill:

• Jonathan Benassaya, Founder & CEO: A melanoma survivor turned serial tech entrepreneur. He previously founded and successfully exited companies like Deezer, StreamNation, and MagicParty. His experience scaling consumer platforms, combined with his personal journey fighting skin cancer, gives SkinBit both mission and proven execution capacity (SKINBIT).
• Dr. Justin Ko, MD, MBA, Co‑Founder & Medical Advisor: Chief of Medical Dermatology at Stanford Medicine. His research on AI in skin diagnostics is widely published, and he remains a practicing clinician. His dual role ensures clinical rigor and real-world applicability (SKINBIT).
• Bill Dower, PhD – Hardware Lead: With a PhD in synthetic aperture radar and experience at Raytheon and Epirus, he’s responsible for SkinBit’s millimeter-wave imaging architecture—critical for their non-invasive scan technology (SKINBIT).
• Manuel Colom – CXO & UX Lead: Former Apple lead designer with decades of UI/UX experience, ensuring the technology is intuitive and centered around patient experience (SKINBIT).
• Ilya Novoselskiy – AI & Computer Vision Lead: A Kaggle Master who won the 2024 Image Collaboration challenge, Ilya designs the core algorithms that differentiate SkinBit’s cancer detection capability (SKINBIT).

This combination—of personal motivation, clinical credibility, imaging hardware mastery, and patient-centered design—felt uniquely well-aligned with scaling a regulated medical product. As a VC-like investor who backs founders first, SkinBit stood out as a team capable of thoughtfully and resiliently navigating the complexities of healthcare innovation.

I Backed SkinBit via Wefunder

I invested on Wefunder, the community-backed capital platform that lets both retail and accredited investors participate in early-stage rounds. SkinBit’s campaign, with a minimum investment threshold of $250, opened the opportunity to align financially—and philosophically—with a mission of democratizing life-saving diagnostics.

The Transformative Future This Represents

This is more than a medical device—it’s an instantiation of the future of preventative care. Imagine networks of SkinBit pods in gyms, pharmacies, and primary care clinics—where early detection becomes a non-negotiable norm rather than a specialized intervention. Over time, SkinBit’s platform could evolve into a comprehensive digital health record for skin, capturing changes across a lifetime. It’s the fusion of AI, imaging, and decentralized infrastructure enabling predictive, accessible, and continuous healthcare at scale.

Absolutely — here’s a revised version of the final section that shifts away from repetition and sales language, and instead focuses on the broader technological and societal implications of SkinBit’s approach.

Why This Fits My Exponential Portfolio Thesis

In My Exponential Portfolio, where I report all my investments, I back founders who:

1. Tackle mass-scale health challenges with technology-first solutions.
2. Demonstrate foundational feedback loops that refine performance and drive growth.
3. Combine practical early execution with a long-term transformative arc.

The long-term potential of SkinBit’s technology lies well beyond dermatology. It represents an early case study in how AI, imaging, and decentralized infrastructure can be brought together to shift diagnostics from reactive to proactive, and from centralized institutions to everyday access points.

Over time, systems like this could normalize longitudinal biometric tracking—not just for skin lesions, but for subtle indicators of other chronic and age-related conditions. With consistent data capture, AI can begin to spot patterns invisible to human perception: slow cellular changes, environmental damage over time, or indicators of systemic illness presenting first through the skin.

If successful, this type of platform may form part of a broader movement toward preventative healthcare—a future where diagnostics run quietly in the background of ordinary life. That’s what excites me most: not just what SkinBit does today, but what this model could unlock across healthcare in the years to come.