SLED Opportunity · NEW YORK · NEW YORK
AI Summary
CUNY seeks an AI-enabled platform to streamline transcript evaluation and credential review for domestic and international admissions, aiming to reduce decision times and improve processing efficiency.
The City University of New York (CUNY) aims to acquire a comprehensive, technology-driven platform that supports the secure, accurate, and efficient processing of both international and domestic academic records required for CUNY applications. The technology must enable CUNY to translate, authenticate, and validate all types of educational credentials and related documents, including those used for undergraduate, graduate, and international admissions. CUNY receives approximately 17,000 international applications each year, processed by Admission Services staff and campus admissions teams using multiple systems and manual steps. Applicants experience lengthy decision times (12–16weeks vs. a target of 6–8 weeks). CUNY’s Process Streamlining team recommends implementing a platform that will provide measurable time savings for Admission Services staff by significantly improving efficiency and replacing manual tasks used to verify transcripts and academic records, calculate GPAs, and determine U.S. equivalency conversions. This will be accomplished through AI-enabled data ingestion, standardization, and calculation models that ensure high accuracy and keep complete audit trails. The goal is to implement a modern admissions processing approach that removes barriers for students, as outlined in CUNY's Strategic Roadmap. Achieving this goal will enable Admissions Services staff to focus on high-value review and decision-making rather than on labor-intensive administrative duties.
SLED stands for State, Local, and Education. These are solicitations issued by state governments, counties, cities, school districts, utilities, and higher education institutions — as opposed to federal agencies.
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