Copyright © 2025 Authors retain the copyright of this article. This article is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

@article{179577,
        author = {SINCHANA B S and Preeti Mondal and Pranavi V and Mrs. Kavyashree G M},
        title = {AI MOCK INTERVIEW PLATFORM},
        journal = {International Journal of Innovative Research in Technology},
        year = {2025},
        volume = {11},
        number = {12},
        pages = {6764-6767},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=179577},
        abstract = {This project introduces an AI-powered mock interview platform that simulates real-world job interviews through real-time voice-based interactions. Users engage with an AI interviewer capable of generating role-specific questions and providing detailed, structured feedback on performance across key areas such as communication, technical skills, problem-solving, confidence, and cultural fit. The platform is built using Next.js, Tailwind CSS, Firebase, Vapi, and Google Gemini, delivering a secure, scalable, and low-latency web application. By offering realistic, accessible interview practice, the system aims to enhance user confidence and readiness for actual interviews},
        keywords = {},
        month = {May},
        }