In the era of transformative AI and Generative AI, tapping into vast data volumes for invaluable insights is a game-changer. But rapid adoption comes with model and usage risks that can lead to potential compliance issues, security vulnerabilities, and reputation damage. Safeguarding against these risks requires complete data visibility and contextual understanding prior to large language model training.

Navigating Generative AI governance isn’t easy. Data scientists, developers, and security teams span different departments. Preparing data means tapping into data lakes and data stores that contain processed or raw data to grasp nuances, exposing your organization to potential leakage risks—particularly with sensitive information scattered across unstructured sources like emails, chats, and cloud storage. Effectively identifying and classifying this data empowers Governance and Security teams to implement proper controls to safeguard sensitive information and ensure compliance.