Outcome/Impact
Michigan Medicine is developing an AI-assisted admissions process that combines traditional models with Maizey’s ability to analyze unstructured data. While initial filtering uses structured data (e.g., GPA, test scores), Maizey adds a critical layer by processing and clustering free-text application materials such as essays to identify meaningful applicant characteristics. This allows reviewers to focus on high-potential and “gray area” candidates rather than spending time on clear admits or rejects. The solution is designed with transparency and bias mitigation in mind, ensuring AI augments rather than replaces human decision-making. This use case highlights Maizey’s strength in turning complex, narrative data into actionable insights at scale.