The Data You Never Collected: Synthetic Data's AI Revolution

Making Data Simple

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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.

●	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."