An Intelligent Resume Builder based on Modern Web Architecture using Generative Artificial Intelligence - Supakorn, Ananya; Kamkaew, Peeyada; Panthong, Rattanawadee (Journal of Applied Science and Innovation, 2026)
This research aims to develop and evaluate an intelligent resume generation system capable of adapting content to specific job requirements by integrating artificial intelligence with a serverless edge computing architecture. The system was developed using Next.js, Tailwind CSS, Hono Framework on Cloudflare Workers, and Cloudflare D1, together with the Gemini 2.5 Flash API for automated resume content analysis, recommendation, and summarization. The results indicate that the proposed system successfully supports the complete resume creation process, including information input, template selection, AI-assisted processing, and PDF export. The system also demonstrated fast response performance through the Cloudflare Edge Network. Overall performance evaluation was at a high level ( = 3.94, S.D. = 1.00) The highest-rated item was the appropriateness of colors, web tone, and font sizes ( = 4.38, S.D. = 0.83), followed by the rapid response of the web application ( = 4.22, S.D. = 0.94), and the accurate real-time resume preview ( = 4.19, S.D. = 1.00). The findings demonstrate that the developed system can significantly enhance resume creation efficiency and highlight the potential of integrating artificial intelligence with modern web applications for future intelligent system development.