To train AI/ML models, you need good data. Agencies also need to protect personally identifiable information, trade secrets, and other confidential information. Traditional methods of synthetic data generation such as rule-based or statistical approaches can be inflexible, limiting the variety and complexity of data they can generate. These techniques can perpetuate biases and produce data that, while statistically similar, lacks realism.