How It Works

Mirage offers mock and synthetic data generation to enable agencies to generate alternative forms of data when the original dataset is too sensitive to use or share, or where more data is needed for software testing or machine learning applications.

• Mock data is created using rule-based approaches, designed to mimic the structure and format of real-world data. It does not require any input data so does not pose any privacy risk, but the resultant data is not highly realistic. Thus, it is more suited for scenarios requiring predictable and repeatable datasets. 
  
  Start generating mock data with our quick start guide.
  (Available through both Web UI and API.)
  
  
  
• Synthetic data is generated using statistical models and gen AI techniques that learn patterns and relationships in real-world data. This requires the user to input data to train the data generation model. This is suitable for scenarios where statistical patterns in an existing dataset need to be retained, or if you require a more realistic dataset.
  
  Start generating synthetic data with our quick start guide.
  (Available through Web UI, API coming soon.)