Making Data Simple
Mar 13, 2026
AI
Startups
Technology
Product
Listen on: Spotify (43 m)
Topics: AI | Product | Startups | Technology
Adam Kamor, co-founder of Tonic.ai, reveals how synthetic data solves the privacy-model training paradox for enterprises and LLM foundries.
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Synthetic data enables safe model training by replacing sensitive information whilst preserving statistical relationships and semantics.
Tonic's approach avoids dimensionality problems by synthesising only sensitive data points rather than entire datasets from scratch.
Fully synthetic structured data for class imbalance problems remains unsolved; simpler techniques like SMOTE outperform complex generative models.
"Our biggest competitor is people incorrectly believing they can build this themselves."