Your sensitive data is everywhere — in federated sources, AI agent pipelines, and analytics dashboards. Data Masking enforces privacy policies at the federation layer — every consumer sees only what governance authorises.
Without governed data masking, these problems compound silently with every new data source and AI deployment.
Multiple masking configurations across environments — production, test, analytics — maintained separately. Policies drift. Exceptions accumulate.
Agents access sensitive data at volume and velocity traditional masking was never designed for — creating exposure that human-centric policies miss.
Regulators require proof — not assurance — that masking is applied consistently, with documented policies and full audit trails, across every consumer.
Sensitive fields identified — PII, PHI, financial identifiers — across all federated sources
Masking rules authored by governance teams — technique, scope, consumer, conditions
Masking applied at federation layer before data reaches any consumer
Dynamic masking by consumer role, context, and consent status — same dataset, different views
Every masking event logged immutably — regulator-ready evidence without additional documentation
Masking rules authored by governance teams — not configured per system. One policy, enforced consistently across all consumers.
Masking applied before data reaches any consumer — human user, AI agent, or application. No post-delivery masking gaps.
Partial redaction, full anonymisation, tokenisation, and format-preserving encryption — appropriate technique for each consumer and context.
Immutable audit trail of every masking application — which rule, which consumer, which fields, when. Regulators can see proof, not just assurance.
See how Data Masking works within the Tantor governed intelligence platform.