InterviewAI

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  Some interactive visuals of our project(Web App) i.e., Interview AI

Inspiration

We observed that many students struggle in interviews not due to lack of knowledge, but because of low confidence, lack of real-time practice, and absence of personalized feedback. This inspired us to create a solution that simulates real interview experiences.

What it does

InterviewAI is a voice-based mock interview platform that conducts real-time interviews, evaluates answers on multiple parameters like clarity and confidence, and provides instant personalized feedback with improvement suggestions.

• How we built it*

We used Next.js and React for the frontend, Django and DRF for the backend, and integrated AI using Google Gemini API. Web Speech API enables voice interaction, while PostgreSQL stores user performance data.

Challenges we ran into Real-time voice processing and synchronization Accurate AI evaluation of answers Maintaining low latency for smooth interaction Integrating multiple APIs seamlessly

Accomplishments that we're proud of Successfully built a real-time voice-based interview system Implemented AI-driven personalized feedback Created a scalable and user-friendly platform

What we learned Practical implementation of AI in real-world problems Handling real-time systems and APIs Team collaboration and rapid problem-solving under pressure

What's next for InterviewAI Company-specific interview modules (Google, Amazon, etc.) Resume-based personalized interviews Advanced analytics and performance insights Integration with placement platforms

Built With

• celery
• channels
• drf
• frontend:-next.js
• jwt
• live-api-database:-sqlite
• postgresql
• react
• redis-ai:-google-gemini-api
• tts
• typescript
• web-speech-api-backend:-django