The database was full of secrets, but none of them were real. Every byte was synthetic, yet every query returned something believable. This was the power of Radius Tokenized Test Data.
Radius uses tokenization to create test data that looks and behaves like production data without exposing sensitive information. This is not masking or simple obfuscation. Each field is replaced with a generated token that is structurally valid and preserves relationships across tables. Foreign keys still map. Joins still work. Validation rules still pass. But there is no way back to the original values.
For engineering teams, this means full-scale testing with realistic datasets while staying compliant with security and privacy requirements. Realistic data shapes catch bugs earlier and remove the risk of scripting fragile mock data. Tokenized test data also scales. From development machines to staging clusters, the size and structure mirror production while the contents remain safe.
Radius Tokenized Test Data integrates directly into your existing data workflows. You can point it at a live database, define tokenization rules per column, and run the process in minutes. It supports complex schemas, nested structures, and multiple data sources. The result: consistent, reproducible test datasets that reflect reality without ever leaking it.