Differential privacy, while not a new concept, provides mathematical guarantees for individual privacy in large data sets. PVML's use of differential privacy means users don't have to alter the original data, reducing overhead and safely unlocking information for AI use. The company's platform allows users to chat with their data without the risk of sensitive data leakage. Other potential use cases include enabling companies to share data between business units and monetizing access to their data to third parties.
Key takeaways:
- PVML, a Tel Aviv-based company, has raised an $8 million seed round led by NFX, with participation from FJ Labs and Gefen Capital. The company offers a solution for analyzing data with the safety guarantees of differential privacy.
- The company was founded by Shachar Schnapp and Rina Galperin, who have extensive experience in computer science, AI, and machine learning. They aim to democratize data by protecting sensitive data and allowing easy access to it.
- Differential privacy, PVML's secret sauce, ensures the privacy of individual users in large data sets and provides mathematical guarantees for that. It allows PVML’s users to avoid making changes to the original data, thus reducing overhead and safely unlocking this information for AI use cases.
- PVML's data analysis tools and platform allow users to chat with their data with the guarantee that no sensitive data can leak into the chat. The company also enables businesses to share data between units and potentially monetize access to their data to third parties.