Sensitive data escaping into ungoverned places — test environments, analytics stores, partner handoffs. Here is how different teams apply the same engine to it.
DSPT and HIPAA coverage for NHS and private health systems where operational data egress is tightly controlled.
PCI-DSS scope reduction, synthetic data for ML pipelines, and enterprise identity integration for regulated financial teams.
Controlled document sharing, AI DLP for client privilege materials, and audit trail for law and accounting.
Scan inbound datasets before publication. Multi-tenant isolation with SDK-first integration.
Eliminate brittle hand-built masking scripts. Statistically faithful synthetic subsets for staging and QA.
Training and evaluation datasets that preserve distribution and correlation without accessing live data.
A 45-minute technical review against one of your real sources answers the fit question faster than any use-case page.