Provision high-fidelity, production-scale test data without ever exposing a single record of real PII.
See how to deliver safe, accurate test data at enterprise scale without code rewrites, duplication, or compliance risk.
Developers need real-world data to test effectively. But the choice is always the same: use real PII and risk compliance – or use fake data and risk production failures.
Blocked from production data, devs test with incomplete samples: bugs slip through, apps fail at scale.
Copying PII into non-prod creates toxic environments: massive compliance gaps, prime targets for attackers.
Manual data prep slows releases. Sanitization is error-prone, costly, and stalls your CI/CD pipeline.
DataStealth delivers safe, realistic, instantly available test data, enabling faster development with zero exposure of sensitive data.
Build test databases in one motion: read from prod, write only de-identified data. Real PII never leaves production.
Tokenization preserves IDs, keys, and relationships so joins and logic work flawlessly.
Automate test data creation inside pipelines. Embed TDM directly into CI/CD and ship faster.
Mirror production schemas, tables, and columns automatically into target test environments.
Read from prod, apply tokenization + masking in-flight, and write only safe data downstream.
Maintain referential integrity across tables and keys, ensuring applications behave as if they’re in prod.
Non-production systems are less secure than production, yet they’re often filled with live PII. DataStealth eliminates that risk by anonymizing production data into meaningful, substituted values that maintain full usability for testing.
Eliminate toxic data exposure in dev, QA, and UAT.
Maintain compliance with PCI, HIPAA, and privacy regulations.
Reduce breach risk while keeping testing realistic.
Our tokenization and masking preserve structure, relationships, and statistical trends of the original data. Applications behave as if they’re running on real production data, but without compliance risk.
Preserve distributions for valid QA, UAT, and performance tests.
Create smaller, targeted datasets while preserving integrity.
Apply multi-table joins and business rules for realistic subsets.
Trigger test data provisioning automatically inside DevOps and CI/CD workflows.
Get expert answers on deploying DataStealth at enterprise scale, without performance trade-offs or rewrites.
Get expert answers on deploying DataStealth at enterprise scale, without performance trade-offs or rewrites.
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