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@article{202187,
        author = {Abhishek Mathur},
        title = {AI-Powered Resume Builder Using Google Gemini Flash Model and Node-React Stack},
        journal = {International Journal of Innovative Research in Technology},
        year = {2026},
        volume = {12},
        number = {12},
        pages = {5925-5931},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=202187},
        abstract = {The resume builder project which is an AI-Powered Resume Builder presents an AI-driven platform to streamline professional resume creation by combining modern web technologies with advanced language models. Leveraging a React/Tailwind CSS frontend and a Node.js/Express backend with a PostgreSQL database, the system uses Google’s Gemini Flash 2.0 API to generate resume content from minimal user input. Generated resumes are immediately displayed in a live editor and evaluated for ATS (Applicant Tracking System) compliance. A companion Telegram bot allows users to retrieve resumes via chat. This paper details the system’s architecture, methodology, and implementation. We demonstrate how AI assistance can greatly reduce the time and effort required to craft high-quality, ATS-optimized resumes. A qualitative evaluation indicates improvements in user efficiency and resume quality, aligning with prior findings that algorithmic writing assistance increases hiring success. The paper concludes with a discussion comparing the AI-aided workflow to traditional resume writing and proposes future enhancements such as multilingual support, LinkedIn integration, and PDF export.},
        keywords = {AI resume builder, Google Gemini, React, Node.js, PostgreSQL, ATS optimization, Telegram bot},
        month = {May},
        }