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Wayam AI
HealthcareEngineeringRepresentative scenario

Automated Synthetic Test Data Generation & PII Masking for Healthcare

A HealthTech platform processing electronic health records (EHR) and insurance claims under strict HIPAA privacy compliance.

Run on Parikshan · Software Delivery & Quality

One protected original block generating anonymous identical replicas

The challenge

    01

    Testing complex claims workflows required realistic patient data sets with diverse medical histories and insurance rules.

    02

    Using production data copies in test environments violated HIPAA regulations and created severe data breach risks.

    03

    Manual creation of complex synthetic test records took weeks and lacked boundary condition variety.

How Parikshan solves it

    01

    Schema & Dependency Learning

    Parikshan analyzes database schemas and relational constraints without reading raw production PII data.

    02

    AI Synthetic Data Generation

    Generates millions of realistic, HIPAA-compliant synthetic patient records, ICD-10 diagnostic codes, and claim histories.

    03

    Edge-Case Data Synthesis

    Synthesizes rare medical condition combinations and complex multi-payer insurance claims for robust testing.

    04

    Deterministic Test State Reset

    Pre-loads fresh synthetic test databases before every test suite run automatically.

    05

    PII Masking Verification

    Audits test database outputs continuously to guarantee zero real PII exposure.

The outcome

HIPAA-compliant testing environment with zero real patient data
0%HIPAA-compliant testing environment with zero real patient data
test data preparation time cut
0 weekstest data preparation time cut
  • 100% HIPAA-compliant testing environment with zero real patient data exposure.

  • Test data preparation time cut from 2 weeks to 3 minutes.

  • Expanded test scenario coverage by 4x using AI-synthesized edge-case patient records.

Representative scenario: a modelled industry situation showing how this accelerator applies. Figures are projections, not a named client result.

Capabilities used

Every accelerator is assembled from the same capability layer, so a workflow you adopt here shares its foundation with the rest of the portfolio.

Bring us the version of this that you actually have.

Every engagement is fixed-scope and outcome-guaranteed. The scoping conversation starts with your systems, not with a template.