This Fast Track SBIR aims to implement comprehensive image anonymization within an enterprise imaging informatics platform built on XNAT. Our vision is for this platform to provide large healthcare enterprises with tools to generate secure research databases at scale that mirror their clinical image archives. These databases would then provide local academic and industry collaborators with a rich resource for clinical research and development of AI-powered applications. Thus, our proposed anonymization services are designed to be scalable, risk-based, and verifiable. The platform's AI-powered image anonymization will include automated detection of PHI using a deep learning based natural language processing engine and automated detection of PHI in image content using a convolutational neural network. The anonymization services will be integrated into Radiologics enterprise and clinical trial XNAT products.