PrepAI is an AI-powered self-interview preparation platform designed to empower job seekers and interviewees in mastering their interview skills. With its advanced natural language processing capabilities, PrepAI simulates real interview scenarios, provides personalized feedback, and offers valuable resources for users to refine their interview techniques and boost their confidence.
Through prompt engineering techniques, PrepAI generates context-rich and relevant interview questions across various domains and job roles. Users can choose their desired interview type, such as technical or behavioral, and engage in a conversational interface to respond to the questions naturally.
PrepAI's AI feedback system analyzes users' interview responses, evaluating their content, delivery, and overall performance. Constructive feedback is provided, highlighting strengths and suggesting areas for improvement, including communication skills, technical knowledge, and problem-solving abilities.
The platform also offers progress tracking features, allowing users to monitor their performance over time. With visualizations and metrics, users can gauge their progress, review previous interview sessions, and track their improvement to focus on areas that require further practice.
With a user-friendly interface and seamless navigation, PrepAI ensures an intuitive experience for users, enabling them to concentrate on their interview preparation without technical hindrances. PrepAI is your comprehensive tool to enhance interview skills, gain confidence, and maximize your chances of interview success.
The Frontend of this site is built using React, Tailwind CSS and Chakra UI. The Backend is built using Node.js, Express and MongoDB.
- There is a signup and signin functionality with fully validated forms to authenticate users along with an option to login via google.
- Users can see their progress and interview history on their dashboard.
- Users can start a new Interview and follow the steps given to seamlessly practice their answers.
- Users will be given personalized feedback and scores for each interview.
- All Interviews, Feedbacks and Scores are saved and an average profile score is shown on the dashboard.
- Users can easily review the entire interview and feedback and in case not needed, there is an option to delete the entire interview from the dashboard as well.
Raghavendra Jingade - GitHub
Kuldeep Negi - GitHub
Manshi Kumari - GitHub
Ruchi Agrawal - GitHub
Kinjal Momaya - GitHub