A.R USIOBAIFO.

The growing complexity of student support services in higher education has created a need for intelligent systems that can provide academic, administrative, and emotional assistance efficiently. This project, titled Designing and Implementing an Autobot Mentor for Student Support, presents the development of an AI-driven chatbot that simulates human-like mentorship interactions using Natural Language Processing (NLP) and Machine Learning (ML) techniques. The system was designed following a three-tier architecture consisting of the presentation, application, and database layers, ensuring modularity, scalability, and ease of maintenance.The Autobot Mentor enables students to access 24/7 guidance through conversational engagement, offering responses to academic inquiries, administrative information, and motivational support. Python and Flask were used for implementation, while MySQL served as the database for storing interaction logs and user data. System evaluation focused on usability, accuracy, and responsiveness, and the results demonstrated that the chatbot achieved
high efficiency and user satisfaction, thereby validating its effectiveness insupplementing traditional mentorship.Overall, this study successfully achieved its objectives by developing a functional AI mentorship system that enhances communication between students and institutions. The Autobot Mentor stands as a scalable model for intelligent academic support systems in digitally transforming educational environments.