This $286,418 Small Business Innovation Research (SBIR) Phase I project, awarded by the National Science Foundation (NSF) under the Technology, Innovation, and Partnerships (CFDA 47.084) program, will develop and validate an innovative artificial intelligence (AI)-assisted mentoring platform to enhance peer mentoring programs in higher education. The project aims to address the critical need for scalable, personalized student support by leveraging large language models and retrieval-augmented generation technology to provide data-informed, evidence-based guidance to students, particularly those from underrepresented backgrounds. The research will focus on technical challenges such as secure data integration, model fine-tuning, and scalable system architecture, with the goal of achieving 90% accuracy in contextually relevant responses and 85% user satisfaction ratings. This project has significant commercial potential, as the mentoring software market is projected to reach $1.3 billion by 2027, and the unique integration of data-driven insights with affordably scaled peer mentoring could provide a competitive advantage in this growing market.
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