MUMBAI, India, June 30 -- Intellectual Property India has published a patent application (202641056843 A) filed by The Principal, Sns College Of Technology on May 05, 2026, for Gen Ai Driven Platform For Domain Based Placement Preparation Mock Testing And Automated Hr Evaluation.
Inventors include G; Dr K Sangeetha; Dr B Vinodhini; Dr A Sumithra; Dr M Shobana; A Indhuja; G Ramesh Kalyan; M Lavanya; S Priyadharsini; P Jacquelin Anushya; Santhosh S; Sarankumar P; Vijayakumar T; and Vilashini V.
The application for the patent was published on June 26, 2026, under issue no. 26/2026.
Abstract: ABSTRACT: A Generative Al-driven platform is disclosed for enhancing domain-based placement preparation, adaptive mock testing, and automated HR evaluation while ensuring secure and efficient data handling. The system includes a user interaction layer (102) and an authentication and security layer (104) for managing secure user access and data flow. A processing engine (106) utilizes Natural Language Processing techniques to evaluate user responses, while an adaptive testing engine (108) dynamically adjusts question difficulty based on performance. The platform further incorporates an automated HR evaluation module (110) that simulates real-time interview scenarios using conversational Al to assess communication and behavioral skills. All user data and performance records are securely managed within a persistence layer (112) using encrypted storage and controlled access mechanisms. The system generates personalized feedback, readiness scores, and skill gap analysis through an analytics layer (114), which are delivered to users via an output interface (116) in the form of interactive dashboards and real-time updates. The invention provides a scalable, intelligent, and secure solution that improves placement readiness and bridges the gap between academic learning and industry requirements. The platform further incorporates a multi-dimensional evaluation and recommendation mechanism that continuously analyzes user performance across technical, cognitive, and communication parameters. Based on this analysis, the system generates personalized learning paths, targeted practice modules, and improvement suggestions to enhance candidate readiness. The adaptive framework ensures continuous progression by identifying skill gaps and dynamically refining assessment strategies. Additionally, the system supports institutional monitoring by providing aggregated analytics and performance insights, enabling educators to design effective training interventions. By integrating intelligent automation with data-driven decision-making, the invention enhances the overall efficiency, accessibility, and effectiveness of placement preparation systems.
Disclaimer: Curated by HT Syndication.
