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Inspiration

Interviews are stressful for both candidates and recruiters. As students, we often struggled with preparing for real interviews and lacked opportunities for realistic practice. At the same time, we noticed that recruiters face challenges in fairly evaluating resumes and assessing candidate performance beyond technical skills. This inspired us to create Prepverse.AI, a platform that bridges this gap by making interview preparation more effective and recruitment more efficient.

What it does

Prepverse.AI is an AI-powered interview and recruitment platform. Candidates can attend dynamic, resume-based mock interviews with voice interaction and face detection, giving them a real interview-like experience. The system provides ATS-style resume parsing and scoring, along with an AI-assisted resume builder to improve job readiness. Recruiters get a secure dashboard to design interviews, analyze performance, and gain meaningful insights beyond resumes.

How we built it

We used React.js + Tailwind CSS for the frontend and Flask + Express.js for backend services. MongoDB stores candidate and recruiter data. The Google Gemini API generates adaptive questions and feedback, while MediaPipe tracks face movement and engagement. Speech-to-Text APIs ensure accurate voice analysis.

Challenges we ran into

Integrating multiple frameworks (React, Flask, Express) smoothly. Ensuring real-time accuracy in speech recognition. Designing a meaningful ATS scoring system. Implementing secure role-based access for candidates and recruiters.

Accomplishments that we're proud of

Building an AI interviewer that adapts to candidate responses. Integrating resume evaluation and resume building in one platform. Delivering a recruiter dashboard with valuable insights.

What we learned

We gained experience combining LLMs, computer vision, and backend systems into a single workflow. We also learned the importance of clean design and scalability for real-time applications.

What's next for Prepverse.AI

Our next steps include multilingual support, an AI recommendation engine for skill improvement, and scalable cloud deployment to support global users.

Built With

• cloud
• deployment
• express.js-database:-mongodb-apis/ai:-google-gemini-api
• flask
• future
• javascript-frameworks:-react.js
• languages:-python
• mediapipe
• on
• platform:
• speech-to-text
• tailwind-css
• web-based