MUMBAI, India, June 22 -- Intellectual Property India has published a patent application (202641070681 A) filed by Srinivasaramanujan Institute Of Technology; Dr. S. Sunitha; Dr. P. Veera Prakash; Mrs. T. Kavitha; Mrs. G. Nagaleela; Mrs. K. Uma Devi; Kiran Kumar G; Tejaswini P; and Partha Sarathi G As on June 05, 2026, for Generative Ai-Based Technical Review System With Secure Proctored Examination.
Inventors include Srinivasaramanujan Institute Of Technology; Dr. S. Sunitha; Dr. P. Veera Prakash; Mrs. T. Kavitha; Mrs. G. Nagaleela; Mrs. K. Uma Devi; Kiran Kumar G; Tejaswini P; and Partha Sarathi G As.
The application for the patent was published on June 12, 2026, under issue no. 24/2026.
Abstract: A Generative AI-Based Technical Review System for Automated Recruitment Evaluation is an advanced recruitment platform designed to automate and improve the process of assessing candidates for technical job roles. The system leverages the capabilities of generative artificial intelligence to create customized technical assessments that are specifically tailored to the requirements of a particular job position. Unlike conventional recruitment methods that rely on static question banks and manual evaluation, this invention dynamically generates questions, coding challenges, and problem-solving tasks based on predefined job descriptions, skill requirements, and competency levels. This ensures that each assessment remains relevant, diverse, and aligned with industry expectations. The system incorporates a secure AI-driven examination environment that maintains the integrity and authenticity of the recruitment process. During the assessment, candidates are monitored in real time through intelligent proctoring mechanisms. These mechanisms utilize webcam-based facial analysis, eye-movement tracking, head-position monitoring, and screen activity observation to detect suspicious behavior or potential malpractice. In addition, encrypted event logging records all examination activities, creating a tamper-resistant audit trail for future verification and compliance purposes. Such monitoring significantly reduces the risk of cheating, impersonation, and unauthorized assistance, thereby ensuring fair and credible evaluations. Another key feature of the invention is its automated evaluation and scoring framework. Candidate responses are analyzed using AI models capable of assessing technical accuracy, coding efficiency, logical reasoning, and problem-solving abilities. The system generates objective scores and performance metrics without requiring extensive human intervention. Beyond simple scoring, the platform performs AI-driven candidate fit analysis by comparing assessment results with job-specific competency profiles. This enables the identification of candidates whose technical capabilities, skill sets, and performance patterns best match organizational requirements. The resulting rankings provide employers with data-driven insights that support informed hiring decisions. The platform is designed to serve multiple stakeholders through dedicated role-based interfaces. Administrators can manage assessments, configure evaluation parameters, monitor examination sessions, and generate analytical reports. Employers can define job requirements, review candidate rankings, and access detailed performance summaries. Candidates benefit from an intuitive assessment interface that provides a seamless examination experience while ensuring transparency and fairness. The role-based architecture enhances system security by granting controlled access to features and data according to user responsibilities. Furthermore, the invention supports scalability and adaptability, making it suitable for organizations of varying sizes and recruitment volumes. The automated generation of assessments, AI-based proctoring, and intelligent evaluation mechanisms significantly reduce the time, cost, and effort associated with traditional hiring processes. By minimizing human bias, improving assessment accuracy, and maintaining examination integrity, the system promotes fair and merit-based recruitment practices.
Disclaimer: Curated by HT Syndication.
