Capisa: A Case-Augmented AI System for Personalized U.S. College Admissions Planning

Abstract

In recent years, demand for personalized and scalable U.S. college admission services is growing rapidly. In response to this, A large number of American college admission agencies have emerged. However, The majority of those American college admission agencies rely on templates, and their college admission guidance lacks personalization, is costly, and relies on manual labor. Accordingly, this paper propose Capisa (College, AI, Path, Initiative, Success, Aspiration), an AI-driven college admissions guidance platform that systematically integrates structured student profile data — including academic records, standardized test scores, extracurricular experiences, and personal inclination—with curated historical admissions cases, and leverages prompt engineering techniques with the ChatGPT-4o-mini model via the OpenRouter API, generating highly personalized, comprehensive planning reports for high school students targeting U.S. universities.

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