MUMBAI, India, Aug. 10 -- Intellectual Property India has published a patent application (202611073711 A) filed by Hello; Prathamesh Desai; Ishita Dcosta; Janhvi Bhandarkar; and Dr. Pradnya Sawant on June 13, 2026, for System And Method For Ai- Based Multi Model Adaptive Interview Assessment (aia) And Behavioral Evolution..
Inventors include Prathamesh Desai; Ishita Dcosta; Janhvi Bhandarkar; and Dr. Pradnya Sawant.
The application for the patent was published on July 31, 2026, under issue no. 31/2026.
Abstract: The present invention discloses a computer-implemented system and method for automated candidate evaluation leveraging artificial intelligence-based human resource technologies. The disclosed system integrates natural language processing (NLP), speech recognition, and computer vision techniques to conduct interactive interviews in a fully automated environment, thereby reducing reliance on manual interviewing processes and minimizing inherent human bias in candidate assessment. A core aspect of the invention is an adaptive evaluation framework configured to dynamically generate interview questions in real time based on continuous analysis of candidate responses and performance metrics. This adaptive mechanism ensures that each interview session is uniquely tailored to the candidate, enabling deeper and more accurate assessment of competency, communication skills, and domain knowledge. The system further comprises a multi-modal assessment engine capable of simultaneously ingesting, processing, and correlating audio, visual, and textual data streams. Audio analysis captures speech patterns, tone, and fluency; computer vision modules analyze facial expressions, non-verbal cues, and engagement levels; and NLP components evaluate semantic content, coherence, and relevance of responses. The integrated output of these modalities produces a comprehensive, quantifiable candidate profile. Evaluation results are synthesized through a machine learning-based scoring pipeline that generates structured reports to assist human resource professionals in data-driven hiring decisions. The system is designed for scalability across enterprise-level deployment, supporting high-volume recruitment workflows while maintaining consistency and objectivity in evaluation standards.
Disclaimer: Curated by HT Syndication.
