Mr. Nagaraju Vassey

https://doi.org/10.64823/ijter.2503003

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

https://doi.org/10.64823/ijter.2501009

This paper presents an AI-powered code review system designed to assist developers by providing real-time, intelligent feedback on software code. The system integrates advanced language models via OpenAI and Hugging Face APIs within a secure Java Spring Boot backend, using AES-256 encryption for data privacy and JWT for secure user authentication. A key feature is its intelligent fallback mechanism: when OpenAI is unavailable, the system seamlessly switches to Hugging Face, ensuring high availability and responsiveness. The frontend, built with React.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 developers by automating routine review tasks while preserving human oversight, ultimately enhancing code quality and accelerating development workflows.