AI-BOT Mock Interviewer

This paper presents an Innovative AI-Bot Mock Interviewer system designed to assist job seeker’s by providing real-time, intelligent feedback on virtual interviews. The system integrates advanced language models via OpenAI APIs within a secure Next.js, Drizzle ORM, and Clerk for secure user authentication. A key feature is its intelligent real time interview feedback mechanism. The frontend, built with Next.js, offers a smooth and interactive user experience. Evaluation results show the system delivers over 90% accurate and relevant feedback, with average response times under 2 seconds. This solution supports people by providing virtual mock interviews while preserving human oversight, ultimately enhancing interview quality and accelerating job seeker’s confidence

@article{ijter2025212505224711,
  author = {Mr. Nagaraju Vassey and Mr. Manne Naga VJ Manikanth and Mr. MANTHRI GANESH RAO},
  title = {AI-BOT Mock Interviewer},
  journal = {International Journal of Technology &  Emerging Research },
  year = {2025},
  volume = {1},
  number = {3},
  pages = {19-24},
  issn = {3068-109X},
  url = {https://www.ijter.org/article/212505224711/ai-bot-mock-interviewer},
  abstract = {This paper presents an Innovative AI-Bot Mock Interviewer system designed to assist job seeker’s by providing real-time, intelligent feedback on virtual interviews. The system integrates advanced language models via OpenAI APIs within a secure Next.js, Drizzle ORM, and Clerk for secure user authentication. A key feature is its intelligent real time interview feedback mechanism. The frontend, built with Next.js, offers a smooth and interactive user experience. Evaluation results show the system delivers over 90% accurate and relevant feedback, with average response times under 2 seconds. This solution supports people by providing virtual mock interviews while preserving human oversight, ultimately enhancing interview quality and accelerating job seeker’s confidence},
  keywords = {Mock Interviewer; Artificial Intelligence; Drizzle ORM; Clerk; Interview Quality},
  month = {Jul},
}

Copyright © 2025 Authors retain the copyright of this article. This article is an open access article distributed under the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.