Discover your skin in one scan

Take a selfie and let our advanced technology analyze your skin.

Within seconds you will gain insight into what your skin really needs.

Do the scan without makeup and in plenty of daylight for the best results!

How it works

Take a selfie and let the tool analyze your skin in seconds.

Direct skin analysis

Our innovative Skin Reader Technology maps the unique characteristics of your skin and detects where improvement is possible.

For best results, scan without makeup!

Insight into your skin needs

From fine lines and wrinkles to dullness, acne, enlarged pores or an uneven skin tone – we show you the areas of concern and your skin's strengths.

Personal advice tailored to your needs

You will immediately receive a personalized skincare recommendation, tailored to the unique needs of your skin.

Scientifically validated technology

The Nomige Face Scan is based on peer-reviewed research in the field of AI-driven image analysis and aging biology. The underlying technology builds on the so-called PhotoAgeClock model, published in the scientific journal Aging. In this study, a deep learning algorithm was trained on more than 8,000 high-resolution facial images and was able to predict chronological age with an average deviation of only 2.3 years. The model identifies subtle morphological features, including micro-wrinkle formation, pigment distribution, and texture changes in the periorbital region, which correlate with biological skin aging.

Methodologically, the Face Scan uses convolutional deep neural networks with transfer learning, based on the Xception architecture. This architecture is a reference standard in computer vision and medical image analysis and is widely used in dermatological AI research. By systematically analyzing millions of pixel values, contrast ratios, and spatial patterns, the model generates an objective and reproducible quantification of skin characteristics.

The scientific basis of AI image analysis as a biomarker for skin and body aging is further supported by multiple publications in, among others, the Journal of the American Academy of Dermatology and additional studies in Aging, as well as research in medical imaging and plastic surgery. This literature consistently demonstrates that deep learning models are capable of accurately and reproducibly detecting age-related skin characteristics, and that in specific contexts they can match or surpass visual assessment by human experts.

The Nomige Face Scan translates this validated scientific methodology into a clinically relevant application for personalized skin analysis, based on objective image data and reproducible algorithmic evaluation.