Sarus natively inserts into existing data infrastructure 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, whether it is Dataiku, Tableau, or your favorite Jupyter notebook.
The Gateway's API is the only way to interact with data. It can be integrated in your data flow in a fully automated manner. Each API endpoint comes with the highest security standards (advanced permissionning, logging) and differential privacy guarantees. The Sarus SDK allows any application to be built on top of the API.
Data protection now has a universal standard: Differential Privacy. No other definition of privacy provides satisfying protection against the risk of re-identification using additional information (e.g.: private or public datasets, triangulation from overlapping requests). Yet, privacy regulations make it clear that it should such 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 derived from sensitive datasets is measured and controlled using the principles of differential privacy.
Sarus builds on top of and extends the most robust implementations of differentially-private. It bundles them into a unified API and provides exhaustive accounting of the output privacy risk. Accounting for all interactions provides truly scalable compliance irrespective of what the data practitioner sets out to do. Only Sarus provides this level of guarantee that all insights are provably resistant to attacks leveraging additional information.