AI-Powered Interview Assistant

Interviews play a crucial role in recruitment and carrier development, yet many candidates struggle due to a lack of structured preparation and constructive feedback. Traditional mock interviews require significant time, effort, and human resources, while existing AI-based solutions often fail to provide adaptive questioning, detailed progress tracking, or domain-specific insights. To address these challenges, this project proposes the development of an AI-powered interview assistant that leverages Gemini to simulate real interview environments. . The system is designed with a React and Tailwind CSS frontend for an interactive user interface, a Flask-based backend for managing communication and logic, and Firebase Firestore for secure storage of user data and reports. The assistant generates domain-specific questions, evaluates user responses, and provides personalized feedback on content quality, clarity, and communication skills. A key feature of the system is its progress tracking and comparison module, which records user performance across sessions and highlights areas of improvement over time. By combining adaptive AI-driven interactions, structured reporting, and user-friendly design, the project aims to create a scalable, accessible, and cost-effective tool for students, job seekers, and professionals to enhance their interview readiness.