This article focuses on the development of an MVP web service for a cosmetic company utilizing internet search technologies, web scraping, and generative artificial intelligence models. The increasing demand for personalized cosmetic products highlights the relevance of this study, which aims to optimize product selection and analysis processes. The research introduces a web service designed to analyze cosmetic products and provide personalized recommendations. The IT architecture, comprising two microservices, was developed and tested on real data. The results demonstrated a recognition accuracy of 99.45% for the company’s products and 92.45% for products from other brands. The overall success rate for data processing reached 92.97%. The proposed solution proves to be effective for creating digital products with minimal development costs and offers potential for further functionality expansion.