Zero Raw PII by Design
Keep sensitive data out of CRMs, apps, processors, and downstream tools. Systems work on governed token references instead of exposed personal identifiers.
Privault is OpenBlockAI’s tokenised data privacy vault for regulated enterprises. It removes exposed personal data from downstream systems, replaces it with governed tokens, and gives teams policy-bound access, audit-ready proof, and stronger control across vendors, partners, and regions.
Keep sensitive data out of CRMs, apps, processors, and downstream tools. Systems work on governed token references instead of exposed personal identifiers.
Control every data reveal by role, purpose, department, partner, geography, and time—so access stays limited, governed, and provable.
Reduce vendor and partner exposure by sharing governed references instead of raw personal data across your external ecosystem.
What starts as one data collection point quickly turns into copies across systems, vendors, processors, and workflows. That creates security exposure, weakens governance, and leaves teams unable to prove who accessed what and why.
Sensitive data gets copied across CRMs, ERPs, partner APIs, analytics tools, support systems, and operational workflows— creating multiple uncontrolled versions with no single control point.
Consent may be captured at intake, but it rarely governs how data is later accessed, shared, reused, retained, or exposed across downstream systems and third parties.
Vendors, processors, and partners often receive more raw data than they actually need—turning every integration into a larger cyber, privacy, and compliance risk surface.
When regulators, auditors, or internal teams ask who accessed a record, which fields were revealed, for what purpose, and for how long—most organizations do not have a clean, defensible answer ready.
Anthem HIPAA settlement — a record HHS OCR resolution tied to a major U.S. health data breach.
Maximum GDPR fine — up to €20 million or 4% of total worldwide annual turnover, whichever is higher.
Individuals affected in the Change Healthcare 2024 breach — one of the largest healthcare cyber incidents in U.S. history.
Privault gives regulated enterprises the control layer missing from modern data operations. It removes exposed raw sensitive data from downstream systems, replaces it with governed tokens, and ensures every reveal is policy-bound, auditable, and controlled across teams, vendors, and regions.
See Privault in ActionWorkflows run on governed token references—not exposed personal identifiers. If a downstream system, vendor, or processor is breached, there is no raw data there to expose.
Every data reveal is controlled by role, purpose, partner, geography, and time. Teams can enforce access policies centrally and revoke access instantly when risk changes.
Every access event is logged with full traceability—who accessed what, which field was revealed, for what purpose, under which policy, and for how long.
Privault uses strong encryption and tenant-level isolation so data stays protected by design, not by assumption—giving enterprises stronger privacy and security foundations.
Choose which data fields require tokenisation, masking, or controlled reveal—along with retention rules, partner restrictions, and policy logic.
Apply tokenisation at the field level—random, deterministic, or format-preserving—before any sensitive data flows downstream. No schema rebuild required.
Bind every reveal to role, purpose, department, partner, geography, and time. Access stays governed, explicit, and revocable—nothing is revealed by default.
Branches, apps, vendors, processors, and internal teams work on governed token references—not raw personal data. Safer integrations, lower third-party exposure.
Keep a searchable, immutable record of who accessed what, which field was revealed, for what purpose, under which policy, and for how long—exportable on demand.
Privault’s tokenisation, policy-bound access, audit trails, and region-aware governance help regulated enterprises align with the data minimisation, security, accountability, and controlled-access expectations of major privacy frameworks worldwide.