Stop exposing production data in lower environments

Copies of production data are one of the biggest and most overlooked security risks in the enterprise.

Production data is typically well protected. The problem is what happens next. Dev, test, analytics, and AI environments all rely on copies of that data — and most of those copies are not adequately protected. In fact, 54% of organizations provide full production backups to development teams (Redgate, 2025), and 68% report unprotected unstructured data (Cloud Security Alliance, 2026).

By the time masking is applied after the data is copied, the risk has already occurred. The sensitive data has left production and is now exposed across your environments.

GenRocket takes a different approach, with a three-phase strategy:

• Protect. Mask sensitive data in place, inside production. Only a protected copy moves downstream, reducing risk at the source.
• Expand. Generate deterministic synthetic data from metadata. No production access needed, and every dataset is traceable to a versioned design.
• Scale. Leverage AI responsibly to simplify the design and delivery of fit-for-purpose synthetic data across the enterprise. No sensitive data reaches a model, and nothing is hallucinated.

Each phase delivers value on its own. Together, they form the Synthetic Enterprise™ — a practical, scalable approach that gives every team the data it needs while keeping sensitive production data where it belongs.

Our new white paper for CISOs explains the risks, the latest research, and a clear roadmap for protecting sensitive production data and transitioning to deterministic data provisioning.