Govern Regulated Data at the Speed and Scale of AI
SEC retention, GDPR residency, and FINRA audit rules assume records sit still. AI regularly moves the same regulated data through a warehouse, a vector index, a stream, and a GPU cluster. VAST enforces encryption at rest, immutability, access control, and audit at the data layer, so governance follows every byte across files, tables, streams, and vectors.
Governance Used to Be a Checkpoint. AI Made It Continuous.
Regulators expect you to prove who touched sensitive data, when, and why, and to keep records intact against tampering and loss. That worked when a quarterly audit could inspect data that had been sitting still. AI pipelines copy the same records across a warehouse, a vector store, a streaming tier, and a dozen sandboxes, and they do it constantly. A control that only checks the state of data periodically cannot govern data that changes location and shape continuously.
Copies Break the Audit Trail
Sensitive records get duplicated into the warehouse, the vector index, and analyst sandboxes. Each copy drifts from its source, and no single system can answer who accessed what, or show a record was never altered.
Residency Rules Fight Global Scale
GDPR and national privacy laws say data stays in-region, but AI training and analytics want it everywhere at once. Enforcing residency across sites and clouds turns into manual policy stitching that auditors distrust.
Retention and Immutability Bolted On
SEC 17a-4 and FINRA demand write-once records and long retention, yet most platforms enforce this in an add-on layer that a misconfiguration or a stolen admin credential can bypass. Proving compliance becomes a forensic exercise.