InfoGenie: RAG-Enabled Intelligent College Helpdesk

Abstract

In today’s higher education environment, colleges and universities are increasingly challenged to provide timely, accurate, and personalized support to students across academic and administrative domains. Traditional helpdesk systems, which rely heavily on human operators or static FAQ databases, often fail to meet the dynamic needs of modern students. They suffer from limited availability, inconsistent answers, difficulty handling peak loads, and high operational costs.
This research introduces an intelligent college helpdesk system based on Retrieval-Augmented Generation (RAG) technology. RAG combines information retrieval techniques with generative AI models to provide context-aware and highly accurate responses. By integrating natural language processing, vector embeddings, and large language models, the system can dynamically search through institutional knowledge bases and generate precise, tailored answers for students.
It effectively handles inquiries spanning academic procedures, course details, administrative processes, campus services, and technical support. Comparative evaluation with rule-based chatbots and human-operated helpdesks confirms the superiority of the RAG-based approach. This study contributes to educational technology by providing a scalable, cost-effective, and high-performing solution to enhance student support services, addressing limitations of traditional systems while ensuring accessibility, reliability, and personalized assistance.