The data was locked behind compliance walls, and the clock was ticking. You needed Hitrust certification. You needed synthetic data generation that could meet it—without slowing you down.
Hitrust defines strict controls for protecting sensitive information, especially in healthcare and financial systems. Synthetic data generation replaces real records with artificial, statistically accurate data, preserving structure and utility while removing identifying details. When engineered to meet Hitrust standards, synthetic datasets let teams develop, test, and deploy without risking protected information.
To align synthetic data generation with Hitrust certification, start with mapped security requirements. Encryption must be applied end-to-end. Access controls must enforce least privilege. Audit logging must capture every action. Data masking alone is not enough—generation must create realistic records that pass validation yet do not trace back to a single real individual.