PRIVACY-BY-DESIGN ANALYTICS & AI

The future-proof way of leveraging sensitive data for analytics and AI

The sarus vault allows secure access

Sarus is the only solution that combines computation on the original data and generation of synthetic data for external use — powered by Differential Privacy.

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SARUS GATEWAY

Privacy-first access to your sensitive data

"Data Cannot be Fully Anonymized and Remain Useful"
(Cynthia Dwork, Godel prize and inventor of Differential Privacy).

From there, the most efficient way to achieve both high utility and strong privacy is to compute on non-anonymized data with guarantees on computation output. Data practitioners benefit from the full data utility without comprising on privacy.

The Sarus Gateway is the fruit of this shared vision.

Deployed Anywhere

Whether on-premises or in public clouds, the Sarus Gateway deploys easily through containerization, and scales smoothly by running on Kubernetes. Sarus is also available in SaaS to kick off data collaborations  without having to deploy anything.

Inherently more secure

The Sarus Gateway inherits all security properties of the original infrastructure and avoid moving data outside of its original systems. All interactions with sensitive data have to go through the Gateway.

Leverage data in full fidelity

Thanks to the mathematical protection of outputs, even the most sensitive data can put to work. Practitioners leverage the full fidelity of their data assets instead of truncated, redacted, or synthetic versions.

FUTURE-PROOF COMPLIANCE

Finest control over data access & full auditing capabilities

Next gen access control for sensitive data
Manage who can access which dataset and what they can do with it with unprecedented precision. Define privacy policies that can be deployed universally irrespective of data sensitivity, user trust, or learning objectives.

Scaling policies with mathematical privacy
Privacy policies should not be guesswork. Instead, use the mathematical framework of differential privacy to have a quantitative and replicable approach to risk management.

Full logging and auditing trail
Each access and each query goes through a gatekeeper that enforces all privacy settings. Every interaction with sensitive information is logged and available for reporting and auditing.

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FUTURE-PROOF COMPLIANCE

Finest control over data access & full auditing capabilities

Next gen access control for sensitive data
Data access used to be all or nothing: very few users would get full access to data, others get nothing. With Sarus, you can manage the full spectrum of privacy protection from truly anonymous synthetic data to full access. It's easy to find the right level for all users and situations.

Scaling policies with mathematical privacy
Privacy policies should not be guesswork. Instead, use the mathematical framework of differential privacy to have a quantitative and replicable approach to risk management.

Full logging and auditing trail
Each access and each query goes through a gatekeeper that enforces all privacy settings. Every interaction with sensitive information is logged and available for reporting and auditing.

SYNTHETIC DATA

High fidelity synthetic samples

Why synthetic data when the original data can be queried?
Maximum accuracy can only be achieved using the original data. Yet, seeing individual rows is very convenient to prepare analyses, design or debug ML models, use data in external code, or even just to get a feel of data. Sarus high utility synthetic data makes it seamless.

Available by default, private by design
The Gateway natively provides synthetic data for all datasets in a fully automated way. This data comes with the mathematical protections of differential privacy.

High quality all the time
The Sarus synthetic data generator beats the state-of-the-art of data generation while adapting to any data structure (tabular, text, images, series of transactions). For more on the architecture that supports our synthetic data modelling, check out our paper.

FULL DATA SCIENCE CONNECTIVITY

Built for all data science workflows

SnowflakeGoogle Cloud Platform

Use any data source
Connect any data source to your Sarus Gateway and make them instantly accessible for analytics and AI applications. It is compatible with tabular data, relational data, time-series, images, text, and more in most common formats.

Compatible with all main data environments and libraries
Sarus supports most data science use cases natively. It leverages existing execution engines (spark clusters, BigQuery, Synapse-SQL, Redshift...) or provides its own. The engines can be leveraged seamlessly from the most common data science environments and ML and BI libraries. The Sarus built-in SDK makes it easy to integrate  remote data seamlessly into your existing workflows.

HOW IT WORKS

Analytics & AI on sensitive data from Day 1

1
Select data source

Select the confidential data source using the Gateway's UI or API. Data types include numerical, categorical, series of events, images, and text. Common data storage and formats are supported.

2
Define user access policies

Define the rules governing the data practitioners’ access to each dataset. Rules templates implement compliance best practices and can be fine tuned to your compliance goals.

3
Use in your data workflows

Authorized data practitioners  connect to the Gateway's API from their favorite environment (python, SQL, etc.). The  SDK lets them work locally on the synthetic data or remotely on the original data in a fully seamless way.

Start unlocking the value of sensitive data assets now!

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