Quality Evolution Platform:

Design-driven, AI-powered, and secure.

GenRocket’s Quality Evolution Platform (QEP) is the industry’s first integrated solution that bridges traditional test data management (TDM) with the most advanced synthetic data generation platform available today. By combining in-place masking, intelligent subsetting, file masking, and design-driven synthetic data generation, QEP gives enterprises complete control over test and training data.

QEP is not a static toolset—it’s a journey. Organizations evolve from reliance on production data, to synthetic-first strategies, and ultimately toward an AI-orchestrated future. This evolutionary approach ensures immediate value while preparing for the next wave of innovation.

Why Quality Evolution?

Traditional test data solutions were built for a slower era. Copying and masking production data may have worked when release cycles were infrequent, but modern enterprises need more. Production data covers only a portion of real-world scenarios, often missing the edge cases and permutations required for full testing. Even when masked, sensitive information can leak, exposing organizations to risk under GDPR, HIPAA, and new privacy laws such as India’s DPDP Act. And with refresh cycles consuming excessive time and storage, teams spend more hours waiting for data than executing meaningful tests.

GenRocket’s Quality Evolution Platform addresses these challenges. It bridges from legacy TDM practices to a synthetic-first future where data is private, comprehensive, and instantly available.

Introducing the Quality Evolution Platform

QEP is not another TDM product. It is an integrated platform designed to help organizations progress along a continuum: starting with masking and subsetting, advancing into targeted synthetic data, and eventually embracing AI orchestration. This phased path ensures enterprises capture immediate benefits while building momentum toward future-state automation and scale.

Synthetic Data Replacement

GenRocket’s advanced masking technology is built on Synthetic Data Replacement (SDR), a process that replaces sensitive values in production databases with controlled and conditioned synthetic data. Unlike traditional masking methods, SDR ensures data cannot be reverse-engineered, is fully compliant with privacy laws, and maintains complete referential integrity across tables.

This approach delivers the best of all worlds—privacy, integrity, performance, and flexibility—while operating at scale with fast, parallel processing.

In-Place Masking

GenRocket’s journey begins with in-place masking. Using Synthetic Data Replacement (SDR)—an approach that guarantees data cannot be reverse-engineered—sensitive values are replaced in production database copies. This creates a secure ‘gold copy’ that can be used in lower environments while preserving referential integrity across all related tables.

Key advantages include:

• Millions of rows masked per minute with parallel processing.
• Automatic PII discovery for fast identification and replacement.
• Full referential integrity preserved across systems.
• Broad support for Oracle, MS SQL Server, IBM DB2, PostgreSQL, and MySQL.

Intelligent Data Subsetting

Once secure masked databases are created, organizations can take the next step with intelligent subsetting. QEP enables teams to deliver smaller, focused datasets that are fit-for-purpose, reducing storage costs and eliminating data refresh cycles. Reusable Test Data Projects deliver fresh subsets on demand, aligning with CI/CD pipelines for faster, automated testing.

File Masking

Beyond databases, GenRocket extends masking to files, ensuring compliance across structured and unstructured data. This includes CSV, fixed formats, JSON, ORC, X12 EDI, and more. With file masking, organizations can securely test commercial applications like Guidewire, Workday, SAP, or PeopleSoft, as well as NoSQL environments.

Synthetic Data Generation

The centerpiece of the Quality Evolution Platform is design-driven synthetic data generation. Unlike production data, synthetic data can be designed to represent every possible scenario—edge cases, negative values, and all required combinations and permutations included. This design-driven approach ensures testers are never constrained by data gaps.

With more than 750 intelligent data generators and over 110 supported output formats, QEP provides unmatched flexibility. Synthetic data can simulate structured, semi-structured, or unstructured data environments, always maintaining referential integrity.

AI Orchestrator: The Next Evolutionary Step

Looking forward, the next phase of the Quality Evolution journey is the AI Orchestrator. It represents GenRocket’s vision for how AI will simplify and automate synthetic data design in the future. The orchestrator will provide a natural language interface, enabling teams to describe requirements conversationally and generate executable G-Cases instantly.

Organizations will be able to choose between deterministic design methods and AI-driven design, depending on the skill level of the user (Novice, Intermediate or Advanced) and to ensure GenRocket can meet with internal company AI security requirements. While GenRocket can already integrate test data at the test case level in any testing tool or framework, this integration process will also be automated by the AI Orchestrator in an upcoming release.

The Evolutionary Journey

QEP is deliberately designed as an evolutionary journey. Phase one begins with in-place masking and intelligent subsetting. Phase two expands into targeted synthetic data generation to address specific gaps in coverage. Phase three scales to full synthetic deployment with enterprise-wide access and distributed self-service. Finally, the AI Orchestrator represents the future—an environment where AI radically simplifies design and orchestration of synthetic data for testing and training.

This step-by-step journey ensures organizations can achieve quick wins while strategically building toward long-term transformation.

Why Choose GenRocket?

GenRocket gives enterprises a competitive edge by transforming how test data is delivered. Traditional TDM is limited by slow refresh cycles, privacy risks, and partial coverage. By contrast, QEP delivers real-time, design-driven synthetic data that cannot be reverse-engineered, provides full coverage, and scales seamlessly into automation pipelines.

Feature	Traditional TDM	GenRocket QEP
Test Coverage	50% data coverage	100% data coverage
Privacy & Security	Risk reduction	Risk elimination
Speed	Slow refresh cycles	On-demand, fresh data
Cost	High data storage costs	Low data storage costs
Future-Proof	Manual, legacy processes	Journey to full AI orchestration

Real-World Impact

GenRocket enterprise customers are already transforming with QEP. Some are replacing legacy TDM with secure in-place masking. Others are modernizing QA with on-demand subsets and design-driven synthetic data. Beyond software testing, GenRocket customers are using QEP to generate high-quality training datasets for AI/ML applications—rule-based, statistical, unstructured, and AI-driven. Each step on this journey help our customers build toward greater speed, accuracy, and compliance.

It’s Time to Evolve

The Quality Evolution Platform isn’t just a tool—it’s a roadmap. By starting with production data, advancing into synthetic-first strategies, and preparing for an AI-orchestrated future, organizations can modernize their testing, ensure compliance, and unlock innovation.

Join the companies leading the next generation of test data management. With GenRocket, you can capture immediate value today while preparing for tomorrow’s opportunities.