SECURE DATA AS IT
COMES IN. CONTROL
AT THAT GOES OUT.
EXTEND CONSISTENT PROTECTION TO SAAS PARTNERS.
GATEWAY-BASED PROTECTION FOR EXTERNAL SYSTEMS.
Data Security Gateway (DSG) Integration
Use the Protegrity DSG as a central point to intercept data flows headed for external SaaS applications or partners and apply appropriate protection policies inline.
- Acts as a controlled enforcement point for external data flows
- Centralizes policy application for data leaving the enterprise boundary
- Integrates with protocols commonly used for SaaS and API communication
Inline Protection
(Pre-SaaS/External)
Apply data protection methods like vaultless tokenization or masking to sensitive fields before the data enters the external SaaS platform or is sent to a partner system.
- Ensures sensitive data is not exposed in clear text within third-party systems
- Protection applied dynamically based on centrally configured policies
- Reduces risks associated with third-party data storage and processing
Format-Preserving Protection Methods
Apply protection methods (like format-preserving tokenization) that maintain the original data format, ensuring compatibility and usability within SaaS application fields and workflows.
- Allows protected data (e.g., tokenized credit cards) to work within SaaS processes
- Avoids breaking SaaS application field validation or formatting rules
- Balances strong data security with critical SaaS operational requirements
Centralized Policy Enforcement
Ensure consistent application of enterprise-wide data protection rules. Policies are defined centrally in the Protegrity Enterprise Security Administrator (ESA) but applied locally by the Application Protector within the app context.
- All app-specific policies managed centrally via Protegrity ESA for consistency and simplified admin
- Local enforcement ensures security rules are always applied correctly in context
- Enables granular, policy-based control over who sees clear vs. protected data
APPLY PRIVACY PRESERVATION ANYWHERE IN YOUR ARCHITECTURE.
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Enterprise Data Security
In A Single Platform
data lifecycle—including for analytics and AI.
Discovery
Identify sensitive data (PII, PHI, PCI, IP) across structured and unstructured sources using ML and rule-based classification.
Learn MoreGovernance
Define and manage access and protection policies based on role, region, or data type—centrally enforced and audited across systems.
Learn moreProtection
Apply field-level protection methods—like tokenization, encryption, or masking—through enforcement points such as native integrations, proxies, or SDKs.
Learn morePrivacy
Support analytics and AI by removing or transforming identifiers using anonymization, pseudonymization, or synthetic data generation—balancing privacy with utility.
Learn more