Web-based selector-Applicant simulation software

The interviewing process is inherently complex and demands an unbiased, objective approach to assess and identify the right talent effectively. This project proposes a web application to enhance the interviewing process using AI technologies like deep learning and Natural Language Processing (NLP). The platform simulates a Board Room environment, starting with ice-breaking questions and advancing to specialized queries tailored to the candidate’s expertise. A key feature is an AI-driven scoring system that evaluates the relevance of interview questions and the quality of candidates’ responses, ensuring a focused assessment of required skills. Utilizing a MySQL database for scalability, the application provides fair and quantifiable evaluations for both interviewers and candidates, helping organizations streamline hiring, reduce bias, and improve workforce quality.