The project aims to enhance the EdTech Platform by transitioning from a basic mentor

prototype to a sophisticated AI-driven Mentor system. Advanced AI/ML students will integrate a Large Language Model (LLM) into the platform using the OpenAI API or a similar LLM. This integration will enable dynamic and interactive mentorship tailored to young learners.

The system will feature multiple mentor personalities, such as a long-term planner who asks reflective questions and a fast-paced mentor who provides direct solutions. The project will also involve refining prompt frameworks and scripts, provided by Masters in Education

students, to ensure that the AI Mentor's responses are age-appropriate, engaging, and

educational. The ultimate goal is to create a functional, interactive mentor system that

enhances the learning experience for young entrepreneurs.

The deliverables for this project include the integration of an LLM with the Unity-based mentor system, enabling seamless text-based interaction. The team will implement a multi-personality framework, allowing for real-time switching between at least two distinct mentor personalities. Additionally, the project will involve prompt tuning and testing to ensure the AI Mentor's responses are supportive and educational. Finally, the team will deliver a fully integrated, functional AI Mentor system, complete with documented architecture and usage guidelines for future expansion.