DataStealth
Test Data Management

Safe, Production-Quality Data for Every Non-Production Environment.

Give DevOps and UAT teams realistic data without ever exposing the real thing.

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prod → anonymize in-flight → non-prod
PRODUCTION
real PII
DATASTEALTH
tokenize + mask
DEV / QA / UAT
safe, realistic

Is Your Development Lifecycle Creating Hidden Risk?

Developers need real-world data to test effectively, but that usually means a tradeoff: use real PII and risk compliance, or use fake data and risk production failures. DataStealth delivers safe, realistic, instantly available test data, enabling faster development without exposing sensitive data.

How it works

Schema Move

Recreate the source database structure, tables, columns, constraints, and indexes on the target before any row-level transformation begins.

Data Move

Read from source, apply protection rules in transit, write a protected copy to the destination. No intermediate unprotected copy ever lands on disk.

Preserve Relationships

The same input value always produces the same output token, preserving joins, foreign keys, and application logic across every table.

Feature set

High-Fidelity Data, Not Just Masked Values

Names, dates of birth, phone numbers, emails, SSNs, postal codes, and card numbers are all replaced with format-preserving, statistically realistic substitutes, while referential integrity holds across every table that references them.

Selective Data Transfer

Scope jobs to specific schemas, tables, or rows using include/exclude patterns and custom SQL filtering.

Lookup & Context Resolution

If John Doe becomes Alex Smith, every table that references him, call logs, disbursements, documents, updates consistently.

Referential Integrity

The same substitute value replaces an original value everywhere it occurs, preserving joins and foreign key dependencies.

Conditional Masking Logic

Apply rules based on column value, lookup value, or context, with combined AND/OR/NOT logic for precise targeting.

CI/CD Integration

A REST API lets Jenkins, GitLab CI, and GitHub Actions trigger refreshes programmatically, with cron scheduling and job chaining.

No Plaintext Exposure

A single-pass streaming pipeline means production data is transformed in transit and never staged in plaintext.

substitution examples
NAMESteven JonesRobert Smith
DATE OF BIRTH1984-03-111958-11-27
PHONE(416) 555-0142(902) 555-7731
EMAILs.jones@acmeinc.comtestdemo@acmeinc.com
SIN / SSN046 454 286731 902 118
CARD NUMBER4539 1488 0343 64675127 3396 8814 7059