AI as a Nail Technician’s Assistant: Personalized Design and Color Selection based on the Client’s Skin Tone and Style

Citation: Mariia Khidirbekova, "AI as a Nail Technician’s Assistant: Personalized Design and Color Selection based on the Client’s Skin Tone and Style", Universal Library of Innovative Research and Studies, Volume 02, Issue 03.

Copyright: This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

The study aims to describe the characteristics of integrating cognitive-analytical artificial intelligence systems into nail service practice to enhance service personalization and ensure safety. The relevance of the topic arises from the convergence of growing demand for hyper-personalized solutions in the beauty industry and the need to minimize biological risks associated with low-quality materials and excessively invasive techniques. The objective is to formalize a comprehensive AI-assistant model capable of performing a multifactorial analysis of individual client parameters (skin shade and undertone palette, stylistic preferences, anamnetic data such as allergies and nail-plate condition) and, on this basis, generate expert recommendations for design and color-scheme selection of nail coatings. The methodological framework is grounded in a systematic review of contemporary publications in the fields of computer vision, machine learning, dermatology, and polymer chemistry, as well as in the integration of an original gentle cuticle-treatment technique. As a result, a multicomponent AI-system architecture is presented, comprising subsystems for visual analysis, natural-language processing, and predictive analytics, all utilizing a specialized database of safe materials. The scientific novelty resides in the proposed holistic approach that unites algorithmic aesthetic personalization with analysis of materials’ chemical compatibility and advanced manual techniques. The practical significance of the research is underscored by its value for nail service professionals, beauty-salon owners, software developers in the industry, and researchers in applied AI.

Keywords: Artificial Intelligence; Nail Services; Personalization; Computer Vision; Color Selection; Skin Tone; Machine Learning; Materials Chemistry; Safety in the Beauty Industry; Nail Art.

https://doi.org/10.70315/uloap.ulirs.2025.0203006