MUMBAI, India, Oct. 12 -- Intellectual Property India has published a patent application (202641118356 A) filed by Sns College Of Technology on October 03, 2026, for Ai-Based Unified Trust, Priority And Verification Platform For Institutional Ecosystems.
Inventors include Ms. N. Ramya Devi; Mithru B; Sanjai Krishnan K; Mugilan V; Nitheesh Raj A M; Mukilan R; Mukund P; Sakthivel K; Priyanka Krishnan K; and Vasantha Kumar B.
The application for the patent was published on October 09, 2026, under issue no. 41/2026.
Abstract: The proposed invention is a Unified Trust, Priority and Verification Platform (“EduTrust-UIP”) designed to improve decision-making, response speed, authenticity, and accountability across three interconnected domains of an institutional ecosystem: customer/student support ticketing, career and institutional guidance, and classroom attendance management. Rather than treating ticket prioritization, career/college/company verification, and attendance integrity as three unrelated tools, the system establishes a single AI-driven architecture that generates a dynamic, evidence-based status a Priority Status for support tickets, a Trust Status for colleges, schools, and companies referenced in career guidance, and an Integrity Status for attendance records by continuously analyzing text, metadata, verification events, behavioral signals, and anomaly patterns. The platform integrates a shared AI Engine, Natural Language Processing (NLP) Module, Trust & Verification Engine, Anomaly Detection Module, Integration Layer, and Security Framework across all three domains. When a support ticket is raised, the system classifies and prioritizes it as High, Medium, or Low based on text and metadata. When a student uses the career-guidance (Ikigai) module, the system verifies the credibility of referenced colleges, schools, or companies and recommends a suitable career path. When attendance is marked, the system verifies the authenticity of the attendance event, detects proxy attempts, computes real-time attendance percentage, and issues threshold alerts. Unlike conventional systems that solve these problems in isolation using separate applications and separate verification logic, the proposed invention introduces a single, reusable Trust-Priority Scoring Engine and a shared anomaly-detection and verification-event architecture that operate consistently across all three domains, reducing duplication, improving fraud/anomaly detection, and giving institutions one unified dashboard for prioritization, verification, and integrity monitoring.
Disclaimer: Curated by HT Syndication.
