Secure AI and analytics pipelines with Protegrity AI Team Edition
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Platform service: Privacy

USE SENSITIVE DATA WITHOUT EXPOSING INDIVIDUALS.

Anonymize and transform PII, PHI, and other identifiers to power/enable data-driven use cases while meeting global privacy standards.
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PRIVACY FOR AI & ML WORKFLOWS

PRIVACY ENGINEERING FOR CONFIDENT DATA USE

Anonymize sensitive data while preserving analytical value with Protegrity’s Anon solution. Deploy across cloud or on-prem environments to support AI, analytics, and compliance needs.

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Retention Expiration

Anonymize aged customer or transaction records to meet retention policies while preserving historical patterns that are crucial to use cases like fraud analytics or risk modeling.

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Privacy-First AI/ML

Prepare privacy-safe AI training datasets by anonymizing sensitive attributes before model ingestion, maintaining performance while minimizing privacy risks like memorization.

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Secure Internal Data Sharing

Confidently share behaviors or analytics datasets between internal teams or departments by removing direct identifiers to prevent accidental privacy breaches.

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Healthcare Analytics

Enable HIPAA-compliant cohort analytics, clinical research, and outcome studies by applying advanced anonymization techniques to sensitive patient data.

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Cloud Data Lake Protection

Apply anonymization before writing to cloud storage (e.g., S3, Azure Blog) to prevent sensitive data exposure in data lakes.

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Selective Operational Anonymization

Target and anonymize specific records within operational databases (e.g., based on user consent status or data expiration) while leaving active records untouched.

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Online Demo

Accelerate data access and turn data security into a competitive advantage with Protegrity’s uniquely data-centric approach to data protection.

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Key Capabilities

ADVANCED PRIVACY PRESERVATION TECHNOLOGIES

Explore Protegrity’s privacy-enhancing technologies (PETs) designed to de-identify effectively while maintaining statistical utility and analytical value.
01
Advanced Anonymization
Remove or generalize identifiers using proven techniques that support rigorous privacy models like k-anonymity, l-diversity, and t-closeness, employing various generalization strategies.
02
Auto-Anonymization
Accelerate the setup process for complex datasets by automatically detecting quasi-identifiers (attributes that could indirectly identify individuals) and suggesting suitable anonymization approaches.
03
Selective Record Anonymization
Precisely apply anonymization at the row level, directly within relational databases. Ideal for enforcing record-specific requirements like retention policies while preserving database integrity.
04
Risk & Utility Metrics
Quantify the risk of re-identification using built-in scoring models (e.g., prosecutor, journalist attacks) and measure the impact on data utility to make informed decisions balancing privacy and usability.
05
API & SDK Deployment
Integrate privacy controls seamlessly into automated pipelines (CI/CD, ETL/ELT, MLOps) using a flexible REST API and Python SDK for job control, scoring, metadata access, and results retrieval.
06
Deployment Flexibility
Deploy powerful privacy capabilities where you need them, with robust support for cloud-native environments (AWS EKS, Azure Kubernetes Service), on-premises infrastructure, and major data platforms.
    ENFORCEMENT POINTS

    APPLY PROTECTION ANYWHERE IN YOUR ARCHITECTURE

    Protegrity’s field-level, format-preserving protection methods can be applied consistently via various mechanisms—Protegrity Protectors—embedded across your data environment. Select the enforcement point(s) that best fits your architecture and specific use case needs.
    EXPLORE ALL PROTEGRITY PROTECTORS
    Native
    Protectors
    Embedded enforcement directly within data platforms (databases, cloud DWH, file systems).
    Proxy-
    based
    Intercept data in transit via gateways or proxies (like DSG for JDBC) without app changes.
    Connectors/
    SDKs
    Embed protection logic directly into custom or third-party applications via APIs/SDKs.
    Batch
    Utilities
    Apply protection transformations offline to files or database tables via scheduled jobs or scripts.

    THE LATEST
    FROM PROTEGRITY

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    Case Studies

    Flexible Data Protection Enables Insurer to Scale Data Analytics in the Cloud

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    EBooks

    Digital Transformation Starts with You

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    PLATFORM SERVICES

    ENTERPRISE DATA SECURITY
    IN A SINGLE PLATFORM

    Explore the additional core services of the Protegrity Data Security Platform.

    Discovery

    Identify sensitive data (PII, PHI, PCI, IP) across structured and unstructured sources using ML and rule-based classification.

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    Governance

    Define and manage access and protection policies based on role, region, or data type—centrally enforced and audited across systems.

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    Protection

    Apply field-level protection methods—like tokenization, encryption, or masking—through enforcement points such as native integrations, proxies, or SDKs.

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    Privacy

    Support analytics and AI by removing or transforming identifiers using anonymization, pseudonymization, or synthetic data generation—balancing privacy with utility.

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    See the protegrity platform in action

    Accelerate data access and turn data security into a competitive advantage with Protegrity’s uniquely data-centric approach to data protection.

    Get an online or custom live demo.

    TRY FOR FREEBOOK A DEMO