Testing quality is only as strong as the data behind it. Our TDM service removes provisioning friction so teams have secure, compliant, and fit-for-purpose test data available exactly when they need it.
Transforming raw and sensitive data into secure, high-utility assets for continuous quality engineering.
Relying only on production data limits your ability to test rare edge cases and future-state features. We use advanced AI models to generate net-new test data from scratch.
Generate realistic datasets that preserve statistical behavior and relational consistency found in production systems.
Create data for negative paths, extreme scenarios, and upcoming features that do not yet exist in production.
Fully synthetic data eliminates exposure to personally identifiable information and compliance risk.
When production-like data is required for complex states, we neutralize sensitive fields while preserving usability for testing.
Apply tokenization, hashing, and obfuscation to sensitive attributes such as names, IDs, and financial records.
Mask consistently across distributed stores so keys and end-to-end business flows stay valid during tests.
Align masking controls with GDPR, CCPA, PCI-DSS, HIPAA, and internal enterprise security policies.
Static datasets become stale and block automation. We treat data as code and integrate provisioning directly into CI/CD.
Deliver environment-specific test data automatically when build and test pipelines are triggered.
Enable developers and QA teams to provision fit-for-purpose datasets in minutes without DBA bottlenecks.
Reset or destroy datasets after runs to prevent contamination and keep non-prod environments stable.
Full production clones are costly and slow. We extract high-value subsets tailored to business and test requirements.
Slice databases into fit-for-purpose micro-datasets driven by rules, journeys, and scenario coverage goals.
Reduce infrastructure footprint and cloud costs by avoiding large full-clone environments.
A phased rollout from assessment to sustainable operations.
Map sensitive data locations, evaluate database relationships, and identify CI/CD integration points.
Deploy enterprise-grade TDM architecture and automation tooling aligned with your stack and governance needs.
Embed data generation and provisioning triggers directly into Jenkins, GitHub Actions, and release workflows.
Continuously update synthetic models and masking logic as application schema and business logic evolve.
Test faster, reduce risk, and ship with higher confidence.
Remove waiting time for manual provisioning and keep CI/CD pipelines running at release speed.
Reduce breach risk in lower environments by preventing unmanaged PII from entering test systems.
Surface hidden defects early by testing against realistic, statistically rich, and edge-focused datasets.
Optimize storage and compute through intelligent subsetting instead of expensive full-database copies.
Our team can assess your current data landscape and design a compliant, CI/CD-native TDM operating model for your platform.