Top Synthetic Data Use Cases for Software Vendors

Test new features early using synthetic data that mirrors production behavior without exposing real data.

• Mirrors real user behavior for early-stage feature testing
• Reduces delays caused by waiting for production data access
• Enables safe, privacy-preserving validation of new functionality

Ensure consistent, safe, and realistic test data across all stages of the software development lifecycle.

• Delivers production-like data for end-to-end testing

• Enables early-stage testing without using real customer data

• Maintains referential integrity across all environments

Modernize systems, migrate to cloud, and implement new workflows with safe, representative data.

• Removes delays caused by data access restrictions

• Enables safe testing of cloud and migration workflows

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• Accelerates validation of digital transformation initiatives

Streamline internal collaboration and external partnerships without exposing sensitive customer information.

• Supports realistic product demos with lesser privacy risk

• Speeds up PoCs, pilots, and onboarding processes

• Enables scalable demo environments tailored to use cases

Deliver immersive product demos, internal training, and academic programs using real-like, risk-free datasets.

• Removes re-identification risks with fully synthetic data

• Enables safe internal and external data sharing

• Helps meet regulatory requirements without blocking innovation

Train and validate AI/ML models with high-quality, privacy-preserving data that reflects real-world complexity.

• Simulates rare scenarios to improve model accuracy and fairness

• Fills data gaps to reduce bias and support explainability

• Accelerates AI development by eliminating manual data prep