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SYNTHETIC DATA

CREATE SAFE DATA.
POWER AI WITH CONFIDENCE.

Protegrity’s synthetic data capability generates realistic, statistically accurate, and privacy-safe datasets that unlock the full potential of AI and analytics. By creating entirely new data that mirrors the patterns of your original datasets—but contains no sensitive information—you can train, test, and scale AI models without risk of exposure or compliance violations.
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WHAT YOU NEED
TO KNOW ABOUT Synthetic Data

What It Is

Synthetic data is artificially generated data that replicates the statistical properties and relationships of real-world data—without including any actual sensitive records.

When to Use It

Use synthetic data when real data is too sensitive, limited, regulated, or biased for safe and reliable use—particularly for AI/ML training, cross-border data sharing, testing in lower environments, and simulating rare events or edge cases that don’t appear in production datasets.

Why It Matters

By removing privacy and availability roadblocks that slow down innovation, synthetic data lets you train and test models at scale, simulate diverse scenarios, and ensure compliance with GDPR, HIPAA, and other regulations. 

The Protegrity Advantage

Why Our Synthetic
Data is Different

Protegrity’s approach goes beyond basic data generation to give you control,
accuracy, and trust:
01
Bias Control
Remove or rebalance skewed attributes for more accurate, unbiased AI outcomes.
02
Model Choice
Select from GANs, diffusion, and other advanced models—with roadmap for BYO model.
03
Customizable Filters
Control input and output with outlier removal, bias adjustments, and privacy thresholds.
04
Data Progression
Adapt quickly as your schema changes without retraining from scratch.
05
Detailed Reporting
Get statistical and privacy reports, including patent-pending re-identification risk metrics.
06
Deployment Flexibility
Run fully under your control—on-prem, in cloud, or hybrid — not locked into a SaaS-only model.

    How Synthetic
    Data Works

    Ingest Sample Data
    Provide a representative dataset (as small as a few rows).
    Apply Models
    Protegrity generates synthetic data using advanced ML methods.
    Customize Outputs
    Configure bias removal, filters, and privacy thresholds.
    Validate Results
    Review detailed statistical
    and privacy reports.
    Use Safely
    Train, test, and share synthetic data with zero exposure risk.

      When Should You Use Synthetic Data?

      Synthetic data is best when you need realistic data without the risks of real data: 
      01
      Training
      AI/ML models in regulated industries like healthcare or finance.
      02
      Testing
      Testing software or integrations
      in lower environments.
      03
      Sharing
      Sharing data across geographies with strict compliance rules.
      04
      Simulating
      Simulating rare scenarios, fraud patterns, or edge cases not present in production.

        Why Use Synthetic Data?

        Synthetic data enables organizations to innovate faster while protecting privacy:

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        Prevent Re-identification

        Fully eliminates re-identification risk.

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        Expand Availability

        Generate unlimited volumes of safe, realistic data.

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        Accelerate AI/ML

        Train models on rich, statistically valid datasets.

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        Reduce Bias

        Create fairer, more balanced datasets.

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        Enable Safe Sharing

        Move data across borders or to/from partners without exposure.

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        Cut Costs

        Replace expensive, hard-to-source, real-world data collection.

        Complete Your AI Security Strategy

        Beyond Synthetic Data: COMPREHENSIVE AI PROTECTION

        Synthetic data complements the other advanced AI data protection capabilities in the Protegrity Platform:

        Text To Analytics

        Ask questions of structured data in natural language, with embedded protection ensuring results stay secure.
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        Semantic Guardrails

        Enforce dynamic, context-aware controls that block unsafe queries and prevent data leakage in real time.
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        Synthetic Data Generation

        Generate statistically accurate, bias-aware datasets that preserve utility without exposing sensitive information.
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        Find & Protect

        Automatically detect and protect sensitive data across ingest, training, and outputs.
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        The Protegrity Data Protection Platform

        Explore Data-Centric Data Protection

        Synthetic Data is part of the Protegrity Platform—delivering centralized policy control, modular capabilities, and data-centric protection across every stage of the AI pipeline.

        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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        Take the
        next step

        See how Protegrity’s fine grain data protection solutions can enable your data security, compliance, sharing, and analytics.

        Get an online or custom live demo.

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