Authors : P. Rajesh; T. Arjun Reddy; Y. Sai Ramana; M. KartheeK; P. Sai Gowtham; P. Sreeshanth; M Charan Sri Sai

Volume/Issue : Volume 10 - 2025, Issue 4 - April

Google Scholar : https://tinyurl.com/3ec35yyu

Scribd : https://tinyurl.com/2pmjd382

DOI : https://doi.org/10.38124/ijisrt/25apr533

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Abstract : This project focuses on creating a Gen AI assistant for college using advanced tools like Retrieval-Augmented Generation (RAG), Natural Language Processing (NLP) and pre-trained transformer models. The Gen AI assistant, called the College-Oriented Intelligence Machine, will assist students with a variety of college-related queries, such as academic information, administrative processes, and campus resources. By leveraging advanced AI technologies, the assistant will understand user questions, retrieve relevant information, and provide clear, accurate responses in real time. This system will reduce the workload on college staff by automating repetitive tasks, such as answering frequently asked student questions. Students will be able to access information anytime, anywhere, improving convenience and efficiency. With its intelligent features and user-friendly design, this Gen AI assistant will make it easier for students to access essential college- related information while enhancing the overall efficiency of college operations.

References :

1. Kumar Shivam, Khan Saud, Manav Sharma, Saurav Vashishth, and Sheetal Patil proposed a chatbot system tailored for college websites, which focused on providing automated responses to commonly asked questions. Their work was published in the International Journal of Computing and Technology (IJCAT), Vol. 5, No. 6, June 2018, pp. 74–77.
2. Janapreethi S., Janapriya S., Sarulatha M., and Dr. G.R. Hemalakshmi presented a chatbot-based enquiry system aimed at simplifying college information access. This was documented in the International Research Journal of Engineering and Technology (IRJET), Vol. 7, No. 3, March 2020, pp. 784–788.
3. Harshala Gawade, Vedika Patil, Prachi Vishe, and Sonali Kolpe developed a conversational chatbot model designed to address student queries. Their research appeared in the International Journal of Engineering Research & Technology (IJERT), Vol. 9, No. 9, September 2020, pp. 741–742.
4. Godavarthi Sri Sai Vikas, Bogala Rahul Roy, Indurthi Deva Kumar, Guttikonda Geetha, and Shaik Ahmad Shareef explored the use of the Multinomial Naive Bayes algorithm for a chatbot integrated with college management systems. The work was conducted in 2020.