Oracle Applications—EBS, JD Edwards, PeopleSoft, and more—are the backbone of enterprise operations. But legacy architectures, customizations, and integrations make testing slow, complex, and risky.
Synthesized delivers secure, production-like test data at scale, so teams working across Oracle can accelerate upgrades, validate integrations, and ensure every release is reliable.
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Challenges and how Synthesized solves them
Legacy complexity and customizations slow testing
Older Oracle environments are highly customized and deeply integrated, making it difficult to create representative test data. Synthesized automates the generation of compliant, production-like datasets tailored to your unique configurations.
Manual data preparation increases risk
Hand-crafted test data is slow, error-prone, and often incomplete. Synthesized automates data provisioning, reducing manual effort and improving test coverage.
Integration testing is inconsistent
End-to-end business processes span Oracle and non-Oracle systems. Synthesized provides consistent, scenario-rich datasets across all systems, improving integration coverage and stability.
Compliance and data privacy requirements
Sensitive business and employee data must be protected to meet GDPR, SOX, and internal audit standards. Synthesized applies automated masking and policy-driven controls, enabling safe, governed access to test data.
Environment sprawl and data drift
Multiple test environments and distributed teams can lead to inconsistent data and duplicated effort. Synthesized standardizes data provisioning with reusable workflows and on-demand refreshes, improving test repeatability and reducing costs.
Manual QA
Manual testing eats up 30% of overall development efforts
Manual, fragmented QA processes force engineering teams to spend valuable time on repetitive tasks—slowing down release cycles and increasing the risk of human error. As software complexity grows, traditional testing methods simply can’t keep pace, leaving organizations exposed to bugs, delays, and mounting technical debt.
Data compliance risks
With regulations changing yearly, fines are no longer an “if” but a “when”
Data privacy and residency requirements are evolving faster than most teams can adapt. Manual compliance checks and legacy test data management tools create bottlenecks, increase the risk of violations, and make it nearly impossible to ensure every release meets global standards—putting your business at risk of costly fines and reputational damage.
High costs
The cost of releasing quality software has never been higher
Manual, fragmented QA processes force engineering teams to spend valuable time on repetitive tasks—slowing down release cycles and increasing the risk of human error. As software complexity grows, traditional testing methods simply can’t keep pace, leaving organizations exposed to bugs, delays, and mounting technical debt.
Financial Services
How UBS advances data privacy and operational excellence with Synthesized
UBS partnered with Synthesized to overcome regulatory bottlenecks and slow, manual test data workflows. By automating the creation of high-fidelity, compliant test data, UBS empowered global teams to innovate faster, reduce risk, and unlock new opportunities for experimentation—all while maintaining the highest standards of data privacy and operational excellence.
70%
Reduction in compliance-related delays for new releases
Zero
Data privacy incidents or regulatory fines since implementation
+40%
Increase in test coverage across global business units
banking & investment
How Deutsche Bank modernizes QA with compliant, scalable test data infrastructure
Deutsche Bank’s Credit Risk Technology team adopted Synthesized to automate the generation of complex, production-like test data for ESG onboarding and beyond. The result: faster, compliant testing, seamless CI/CD integration, and a reusable foundation for future automation—empowering both technical and non-technical teams to deliver with confidence.
80%
Reduction in manual test data provisioning time
3x
Faster onboarding of new regulatory and ESG requirements
+30%
Increase in developer and QA productivity across teams
Why synthesized
Synthesized is built for Oracle Applications
Accelerate Oracle upgrades and migrations
Provision compliant, production-like data on demand to de-risk upgrades, migrations, and new feature rollouts.
Enhance regression testing for every release
Continuously feed test suites with realistic data via CI/CD-native workflows to catch issues before they reach production.
Reduce compliance risk by design
Apply automated masking, anonymization, and audit trails to meet GDPR, SOX, and internal control requirements.
Strengthen end-to-end business process validation
Deliver consistent data across Oracle Applications and connected systems to validate real business scenarios at scale.
Covering Oracle Applications testing needs
High-fidelity data for Oracle EBS, JD Edwards, and PeopleSoft
Generate realistic datasets for core modules—Finance, HR, Supply Chain, and more—aligned to your configurations.
Migration and upgrade support
Standardize data across legacy and modern Oracle environments to validate parity and process changes.
Cross-system integration validation
Provision coherent data for Oracle plus adjacent systems (e.g., Salesforce, Workday) to test end-to-end flows.
Performance and load-ready datasets
Create scaled, representative data volumes to evaluate performance and stability before peak events.
Partners & integrations
Built to work with your ecosystem
We understand that today’s production data pipelines and development environments are complex and dynamic. So while you can use Synthesized to generate production-like data for your specific POC, it also works with your specific technologies.
Data generation for any development and QA use-case
Streamline the database generation process, ensuring the availability of high-quality production-like data for testing while removing manual effort and accelerating development cycles.
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Reduce the risk with codified regulatory rules
Ensure regulatory compliance and reduce risk by encoding masking policies that protect sensitive data from breaches and legal liabilities.
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Access the right data, not all the data
Enable secure, role-specific data access, or create tailored subsets and selectively mask sensitive information to balance usability and protection.
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