MVP Web Service for a Cosmetology Company with Artificial Intelligence Elements

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.

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Publication Details

Journal
Technoeconomics & Management Research
Published
2025-08-28
DOI
https://doi.org/10.57809/2025.4.1.12.6
Primary Topic
Geochemistry and Geologic Mapping
Type
article
Field-Weighted Citation Impact
0.00
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article

MVP Web Service for a Cosmetology Company with Artificial Intelligence Elements

Technoeconomics & Management Research
Geochemistry and Geologic Mapping
article

MVP Web Service for a Cosmetology Company with Artificial Intelligence Elements

article en

Abstract

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.

Technoeconomics & Management Research
University of Nottingham (GB), Peter the Great St. Petersburg Polytechnic University (RU)
Industry, innovation and infrastructure
Openalex Percentile: Top 61%
Geochemistry and Geologic Mapping
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MVP Web Service for a Cosmetology Company with Artificial Intelligence Elements · Technoeconomics & Management Research (2025) | TGRS Research Map | TGRS