In the hectic moments before a job interview, users often experience a range of emotions from nervousness to self-doubt. Traditional interview preparation methods, such as rehearsing responses or seeking advice from friends and mentors, often lack personalized feedback and fail to simulate the dynamic nature of real interview scenarios. Our inspiration for Ai&U stemmed from our collective experiences and user research, revealing common issues like "nervousness," "lack of feedback," and "difficulty answering certain types of questions." Recognizing the growing importance of AI technology, we saw an opportunity to leverage it to create a solution that addresses these shortcomings.
- Personalized AI-Driven Interviews: Users can input their job description and resume to receive specific interview questions.
- AI Avatar Interactions: AI avatars react with expressions based on user responses.
- Voice-to-Text: Translates spoken responses into text for analysis.
- Feedback Generation: Provides detailed feedback on performance, highlighting areas for improvement.
- AI Chat Assistance: Users can ask follow-up questions and receive additional feedback from the AI interviewer.
- Interview Recording: Records interviews for later review with timestamped comments.
- User Input: Users enter their job description and upload their resume.
- AI Preparation: The AI analyzes the information and generates tailored interview questions.
- Live Interview: Users engage in a simulated interview with an AI avatar that reacts to their responses.
- Feedback: After the interview, users receive a detailed feedback report and can interact with the AI for further insights.
- Frontend: Next.js, CSS
- Backend: Node.js
- AI & NLP: Python, Jupyter Notebook
- Design: Figma
- API Integration: Connecting the frontend and backend through API calls was challenging due to our limited experience.
- Real-Time Interaction: Ensuring smooth and realistic interactions between users and AI avatars required significant fine-tuning.
- User-Centric Design: Prioritized user experience throughout the design process.
- AI Avatar Development: Successfully developed and tested the virtual interview avatar feature.
- Comprehensive Feedback: Implemented a robust feedback system that provides personalized insights.
- Importance of Personalized Feedback: Recognized the value of real-time, personalized feedback in improving interview preparation.
- Team Collaboration: Gained insights into effective team management and integrating frontend and backend development.
- Enhanced Personalization: Incorporate users' past interview results to tailor future questions.
- Interviewer Selection: Allow users to choose their AI interviewer based on specific roles or companies.
- Detailed Feedback: Record interviews and provide timestamped comments for specific feedback points.