Sarus natively inserts into existing data infrastructures and workflows, whether it is on-premises or in public clouds. It follows the latest standards for deployment and resource management (Docker, Kubernetes). Data is available to use in the most used data science environments and tools (PowerBI, Tableau) or with the main python libraries.
The Gateway's API is the only way to interact with data. Each endpoint comes with the highest security standards (advanced permissionning, logging) and differential privacy guarantees. An SDK makes it easy to integrate in all applications.
Data protection now has a universal standard: Differential Privacy. No other privacy definition provides satisfying protection against re-identification using additional information (e.g.: using public datasets, overlapping requests...). Yet, privacy regulations make it clear that such a protection is a prerequisite for anonymous information. For instance, GDPR recital 26 specifies that “data which could be attributed to a natural person by the use of additional information should be considered to be information on an identifiable natural person".
At Sarus, Differential Privacy is at the core of all interactions with sensitive data. Whether it is metadata, synthetic data, SQL analyses, or machine learning models, every bit of information coming out of Sarus is measured and controlled using the principles of differential privacy.
Sarus builds on top of and extends the most robust implementations of differential-privacy. It bundles them into a unified API and provides exhaustive accounting of the output privacy risk. This makes compliance truly scalable irrespective of what the data practitioner sets out to do. Only Sarus provides such a native guarantee against attacks with additional information.
