Researchers

Easily Access Patient Data

Fast, Diverse, and Responsibly Sourced Data

Traditional methods of collecting patient data for registry studies are costly to mitigate the risks of data sharing. It can take months to gather enough data for a single study, and the data itself may not be suitable for repeated use in other studies because of restrictive data use agreements and the logistics of moving data. Instead of moving data, SAIL uses High-Assurance federated learning to source data from distributed hospitals to allow for secure access to diverse and unique data.

Complete Compliance and Auditing

Traditional federated learning methods expose valuable research code and proprietary strategy to many different environments. SAIL’s platform has full auditing and protection with the use of trusted execution environments that assure confidentiality and integrity.

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