Case Study: KAUST and research consortium save 1,000+ hours with brighter AI Redact

KAUST - Customer Case Study

king abdullah university of science and technology (KAUST) was part of a major research consortium with Facebook AI Research and other universities to build the world's largest egocentric video dataset. They faced the challenge of needing to anonymize thousands of hours of video to comply with strict privacy laws like GDPR, a task that would have taken countless hours of manual work. They required a fast, accurate, and cost-efficient AI solution capable of handling shaky footage from various cameras and countries.

brighter AI provided its on-premise Deep Natural Anonymization software to automatically redact faces and license plates directly on the clients' servers. This allowed the consortium to anonymize over 3,000 hours of video in a few months. Each university partner saved over 1,000 hours of manual work, ensured global privacy compliance, and protected more than 5,000 visual identities.

KAUST

Bernard Ghanem

Associate Professor