Reseach Computing has developed a multi-agent AI system that processes diverse high school transcripts with 96.7% accuracy, cutting review time from 30 minutes to 45 seconds. Pattern recognition, semantic analysis, and visual intelligence agents collaborate through GPA-based quality signals, ensuring reliability. This scalable, privacy-preserving approach transforms admissions workflows—enabling faster, fairer, and more consistent application evaluations while reducing institutional costs and expanding access.

Our project redefines document automation by applying multi-agent AI coordination, rather than monolithic processing, to one of higher education’s most complex, high-volume tasks: transcript evaluation. It stands out through three novel innovations:

1. Specialized agent collaboration between pattern recognition, semantic analysis, and visual intelligence—coordinated dynamically for maximum accuracy and efficiency.
2. Domain-specific quality control using GPA extraction as a coordination signal—an approach not seen in prior educational AI solutions.
3. Scalable, privacy-preserving deployment that integrates seamlessly into institutional workflows, transforming admissions from labor-intensive bottlenecks into consistent, equitable, and rapid decision-making processes.

This combination of technical novelty, measurable impact, and broadapplicability makes it a model for future AI-powered educationaladministration.

For more information, please email Research Computing at rc@sc.edu.