Create fictitious data to cover every user story, test case and business requirement, available on demand to your entire delivery ecosystem.
Cover every scenario needed for quality
Ensure continuous data availability
Replace sensitive data in lower environments
Generate realistic synthetic data with measurable coverage to deliver superior software at speed,
free from the risk of damaging data breaches and slow data provisioning.
Data discovery
Synthetic data generation
Data coverage
On demand provisioning
Generating data on demand avoids the time wasted waiting for, finding and making test data, while providing data in parallel to avoid clashes.
Delivering software with realistic-but-fictitious data avoids regulatory non-compliance and privacy risks in testing and development.
Synthesising data for every scenario, test, edge case and outlier enables rigorous development, finding bugs while they remain low impact.
Automatically generating data on demand avoids the labor costs and toil associated with finding and making complex test data.
Across industries and in complex environments, some of the world’s largest enterprises use the Curiosity platform to generate rich data on demand.
AI is making system data more complex than ever. Developing AI-driven, AI-built systems requires diverse data that reflects intricate relationships, trends and hierarchies. Model-based data generation is perfect for overcoming this complexity.
Principal Test Data Engineer
Read a resource, or meet with an expert, to learn how synthetic data generation can build quality, productivity and privacy throughout your entire delivery ecosystem.
Rich synthetic data, available on demand across your entire enterprise
