Research on the quality of artificial intelligence platforms
Students Name: Horbatyi Nazar Romanovych
Qualification Level: magister
Speciality: Quality, Standardization and Certification
Institute: Institute of Computer Technologies, Automation and Metrology
Mode of Study: full
Academic Year: 2025-2026 н.р.
Language of Defence: ukrainian
Abstract: This master’s thesis is dedicated to developing a comprehensive methodology for assessing the quality of artificial intelligence platforms. The relevance of the study is driven by the rapid development of the AI solutions market, where potential users face the challenge of making a justified choice of the optimal platform due to the lack of unified evaluation standards that consider the entire spectrum of modern requirements. The aim of the work was to create a unified tool for a comprehensive comparison of the quality of heterogeneous AI platforms. To achieve this, an analytical review of the current market and existing evaluation approaches was conducted, revealing their fragmented nature. Based on this analysis, an original methodology was developed, which for the first time integrates six key categories of criteria: technical characteristics, functional capabilities, MLOps maturity, ethical aspects, economic factors, and the specifics of generative AI. The methodology includes a detailed evaluation matrix, standardized checklists, and testing procedures. The practical value of the development is confirmed by experimental research, during which eight popular platforms were tested and compared, including ChatGPT, Gemini, GitHub Copilot, Midjourney, and others. The experiment not only demonstrated the effectiveness of the methodology but also identified clear leaders across different categories, providing users with objective benchmarks for selection.