TalentLens: An AI-Powered Resume Screening and Candidate Ranking System

ABSTRACT The rapid growth of digital recruitment platforms has resulted in a large volume of job applications, making manual resume screening inefficient and prone to bias. This paper presents TalentLens, an AI-powered resume screening and candidate ranking system designed to automate the initial stages of recruitment. The system uses artificial intelligence and natural language processing to extract information from unstructured resumes and compare them with predefined job requirements. TalentLens supports multiple AI providers to perform contextual analysis and generate percentage-based match scores. The system is implemented using a full-stack architecture with React for the frontend, Spring Boot for backend services, and AI APIs for intelligent processing. Experimental results show that the system significantly reduces screening time while ensuring consistent and objective candidate evaluation. Key words: Resume Screening, Artificial Intelligence, Recruitment Automation, Natural Language Processing, Candidate Ranking, Decision Support Systems