Use Cases
AI feature development on realistic data without PHI/PII risk. Load testing with realistic distributions. Edge-case generation for rare intents. Regulatory audits where real data can’t be shared.
Tool Landscape
Tonic.ai, Gretel, Mostly AI — enterprise-grade. Salesforce Data Mask — on-platform generation. SDV — open source. Each with strengths: Gretel strong on generative; Tonic on relational; Salesforce native for SF-specific workloads.
Privacy Posture
Synthetic data isn’t automatically private. Poorly-trained generators can leak training examples. Differential privacy techniques help. Verify your provider’s privacy guarantees; don’t assume.
AI Testing Specifics
Need synthetic conversations, not just records. Realistic intent distributions, message patterns, edge cases. Generate thousands, not hundreds — low-volume synthetic data tests rare behavior poorly.