PrepWise: Smart Interview Preparation Platform

Abstract

Preparing for job interviews can be really tough for students and people looking for a job. It takes a lot of practice and feedback to get good at it. Usually people just read questions or practice by themselves. That does not really help them improve. This is where PrepWise comes in. PrepWise is a platform that uses artificial intelligence to help people prepare for job interviews [3]. It is like an interview but it feels real. PrepWise can make interviews based on the kind of job you want how experience you have and what technology you know. When you use PrepWise, a computer program asks you questions like a person would in a job interview. It records what you say and then gives you feedback on how you did. It tells you how well you communicated how good your technical skills are, how confident you seemed and how well you solved problems. The people who made PrepWise used something called the stack to build it. This includes things like MongoDB, Express.js, React and Node.js. They also used some technologies to make sure the platform is easy to use and works well. PrepWise is a tool for people who want to get better at job interviews. It is, like practicing with a person but it is a computer program.

Introduction

It begins by explaining that many job seekers struggle in interviews due to lack of preparation, nervousness, and limited real-world practice. Traditional methods like reading questions or watching videos are not interactive or personalized. To address this, PrepWise uses artificial intelligence to simulate real interview experiences and provide instant feedback.

The system includes key modules such as user authentication, AI-based interview question generation based on job role and skill level, and a chatbot that conducts mock interviews. After the session, NLP techniques analyze user responses for clarity, relevance, and structure, and the system generates a detailed performance report highlighting strengths and areas for improvement.

Technically, the platform is built using the MERN stack (MongoDB, Express, React, Node.js) with Tailwind CSS for UI and Gemini API for AI-based question generation and evaluation. It requires standard computing resources and a stable internet connection.

Experimental results show that the system generates relevant questions, provides fast feedback, and helps users improve communication and problem-solving skills. Users reported increased confidence after repeated practice sessions. However, challenges remain in understanding vague responses, adapting to specialized domains, and fully replicating human-level judgment in evaluation.

Conclusion

PrepWise has a platform that helps people get ready for job interviews. This platform uses computer intelligence to make interviews that feel real [3]. It helps people practice answering behavioral questions. The system uses computers to make the learning fun and see how well the person is doing. PrepWise is thinking about making the platform even better. They want to add things like special learning plans for each person tests to see how good someone is, at coding and better computer models to judge the interviews. They also want to make a version that works on phones. PrepWise platform will keep getting better with these features.

References

[1] M. Roy and K. Singh, “Job Recommendation System Using Hybrid Filtering Approach,” Elsevier Procedia Computer Science, vol. 199, pp. 305–311, 2023. [2] L. Sharma and P. Desai, “Automated Resume Screening Using Machine Learning Techniques,” International Journal of Computer Applications, vol. 182, no. 48, pp. 30–34, 2022. [3] S. Gupta and R. Mehta, “AI-Based Interview Chatbot using NLP,” International Journal of Engineering Research & Technology (IJERT), vol. 10, no. 7, pp. 120–125, 2021. [4] Gemini API Documentation, “ChatGPT and Language Model API”

Copyright

Copyright © 2026 Mr. Nishant Gathani, Mr. Ganesh Gupta, Mr. Nikunj Sarvaiya, Mr. Siddhesh Gawade, Mr. Ashraf Siddiqui. This 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.