A Real-Time AI-Based Smart Interview Platform for Scalable and Automated Recruitment
Year: 2026
Type: conference-paper
Abstract: The recruitment process over the past years has been challenged by the huge number of job applicants whose number has been increasing exponentially, causing inefficiencies in resume screening and interview management process. Manual shortlisting is both costly and discriminatory besides being unrealistic in case of large scale hiring. This paper introduces an AI-based platform of a placement assistant, which is an automated resume screening, interview scheduling, performance evaluation, and job recommendation platform based on dual-role architecture tailored towards students and HR managers. The system is a combination of full-fledged frontand back-end with a secure database management system that makes it possible to analyses resumes according to the needs of a company, conduct interviews in parallel, and provide realtime performance reporting. Resume parsing, ranks and interview evaluation are done using advanced AI models, which guarantees objective and data-driven recruitment. The suggested system saves the HR workload greatly, enhances the accuracy of the candidate-job matching, and facilitates the hiring process at a large scale, as it enables conducting multiple interviews concurrently. Experimental analysis has shown to be more efficient, more scalable and more precise than the traditional recruitment processes. The platform provides one of the best solutions to contemporary recruitment issues and is an extensively scalable framework of AI-assisted hiring systems.
Institution: DY Patil Deemed to be University
Language: English
Topic: AI and HR Technologies
Domain: Social Sciences
Open Access status: hybrid
OpenAlex ID: W7204841017