SkinBit has raised $6 million in pre-seed funding to expand a technology platform designed to make full-body skin imaging more accessible and give patients a consistent record of how their skin changes over time.
The round includes investments from Boost VC, Cleo Capital, Manna Ventures and Profluent Capital, alongside Lyft co-founder Logan Green and nine board-certified dermatologists. Rather than relying on a single annual visual examination, SkinBit combines standardized imaging, computer vision and dermatologist review to create a patient-owned, longitudinal skin health record.
Disclosure: I am an investor in this funding round.
Turning a Skin Examination Into a Repeatable Dataset
Most skin examinations provide a snapshot of what a dermatologist can observe during a specific appointment. Without standardized images from previous visits, clinicians may have limited information for determining whether a lesion is new, growing or otherwise changing.
SkinBit is attempting to make that process more systematic. Its platform records the location, dimensions and visual characteristics of notable marks, then links that information to images captured during subsequent visits. This allows dermatologists to compare the same areas of a patient’s body over time rather than depending entirely on memory, patient photographs or notes from earlier examinations.
The company’s central premise is that the second scan may be more clinically useful than the first. An initial examination establishes a baseline, while later scans can reveal changes that may warrant closer evaluation.
How SkinBit’s Screening Model Works
A SkinBit appointment consists of an approximately 20-minute, in-person imaging session conducted by a trained technician. The company uses high-resolution photography and cross-polarized light, which reduces surface glare and allows finer skin details to be captured under controlled conditions.
The imaging protocol covers 15 anatomical regions and includes dermoscopic close-ups of notable marks. The resulting images and structured metadata are then reviewed by a board-certified dermatologist. Patients typically receive a written assessment through the SkinBit application within 48 hours, with referrals available when additional examination or a biopsy may be appropriate.
Computer vision is used to organize the images, support year-over-year comparisons and help dermatologists focus their attention. Importantly, SkinBit says the software does not make the final clinical determination. Every scan is reviewed by a dermatologist, who remains responsible for recommendations and decisions about follow-up care.
The company also states that its imaging system documents the surface of the skin and is not itself intended to diagnose, treat, cure or prevent disease. Skin cancer screening and diagnosis remain the responsibility of licensed medical professionals.
Bringing Specialized Imaging Into Existing Clinics
SkinBit plans to place its scanning systems inside dermatology practices, longevity clinics, med spas and other wellness destinations. This partner-based strategy could allow the company to expand without constructing a large network of standalone medical facilities.
According to its website, approximately 220 square feet can be converted into a SkinBit imaging center. The company supplies the equipment, standardized imaging environment and dermatologist review service, while the partner provides the physical location and access to patients or members.
SkinBit expects to have three locations operating in 2026 and 15 by the end of 2027. The company also reports that more than 20 prospective locations are in active discussions and that over 5,000 people have joined its waitlist.
This distribution model could help address some geographic and scheduling barriers associated with dermatology, but it also creates operational challenges. SkinBit will need to maintain consistent lighting, camera calibration, patient positioning and image quality across every partner location. It will also need reliable referral pathways so that patients with concerning results can access appropriate follow-up care.
Building the Imaging Infrastructure for Dermatology AI
SkinBit’s longer-term opportunity may extend beyond the scanner itself.
Artificial intelligence systems in medical imaging depend heavily on the quality and consistency of the data used to develop and evaluate them. In dermatology, photographs can vary substantially based on the camera, lighting, angle, distance, skin preparation and imaging protocol.
SkinBit is building a standardized acquisition system that captures images under repeatable conditions. Its technical work includes high-resolution multi-camera imaging, controlled illumination, polarization, camera calibration, three-dimensional reconstruction and the preparation of images for downstream computer vision analysis.
A growing collection of structured, longitudinal images could eventually become a valuable foundation for developing systems that identify subtle changes or help prioritize lesions for review. However, building a large dataset is not sufficient on its own. SkinBit will still need to demonstrate that its models perform consistently across different skin tones, body types, age groups and clinical settings.
The company must also establish clear standards for privacy, patient consent, data portability and the use of images in future model development. These questions become increasingly important when a platform is designed to retain highly sensitive medical images over many years.
A Company Shaped by the Founder’s Own Diagnosis
SkinBit CEO and co-founder Jonathan Benassaya previously co-founded music streaming service Deezer and held senior product roles at Life360 and Meta. His decision to build SkinBit followed his own melanoma diagnosis in 2020, when a dermatologist noticed a lesion beneath his mask near the end of an appointment.
The company has assembled a clinical team that includes Dr. Justin Ko, Chief of Medical Dermatology at Stanford Hospital, and Chief Medical Officer Dr. Sancy Leachman, the former chair of dermatology at Oregon Health & Science University and creator of the MoleMapper research initiative.
The participation of nine dermatologists in the funding round provides SkinBit with practitioners who have a direct interest in evaluating how the platform works in real clinical environments. That support is a useful early signal, although broad adoption will ultimately depend on clinical evidence, workflow integration and measurable improvements in patient care.
The Next Test Is Execution
The $6 million round gives SkinBit additional resources to bring its first locations online, refine its imaging system and begin building the longitudinal dataset behind its platform.
Its approach represents a different application of artificial intelligence in healthcare. Rather than positioning software as a replacement for a specialist, SkinBit is using computer vision to improve the information available to dermatologists and make examinations more consistent from one visit to the next.
The immediate test will be whether the company can reproduce that experience across a distributed network while maintaining clinical quality and giving patients timely access to follow-up care. If it succeeds, SkinBit could help move skin screening away from isolated annual snapshots and toward a more continuous, data-driven model.