The organization is seeking a vendor to provide an enterprise-wide synthetic data generation solution. The required solution should utilize Generative Artificial Intelligence (GenAI) algorithms to produce artificial datasets that accurately reflect the statistical properties, patterns, and relationships of original datasets, without incorporating any personally identifiable information.

This technology will accelerate AI model training, enhance software testing, and facilitate data sharing while adhering to privacy regulations. Currently, anonymized production data is used and periodically refreshed for non-production environments; the new solution should improve upon this by generating synthetic datasets as needed.

The proposed solution must support a variety of database systems, including DB2, SQL Server, SQL Managed Instance, and Oracle, to accommodate a range of workloads. Additionally, the solution should permit customization of data attributes such as volume, distribution, and temporal patterns for varied use cases. The system must allow for scalable data volumes to meet different testing requirements while preserving referential integrity, business rules, and statistical fidelity.