Privacy

Synthetic data is artificially annotated information that is generated by computer algorithms or simulations, commonly used as an alternative to real-world data.

How our new Synthetic Data Accelerator Program with AWS will help enterprises scale responsible AI systems fast.

How differential privacy can generate provably private synthetic text data for a variety of enterprise AI applications.

Beta2 for Gretel.ai is all about delivering privacy engineering as a service through clean, simple APIs.

A look at how using Gretel’s Privacy Filters to immunize synthetic datasets against adversarial attacks can impact machine learning accuracy.

Everything you need to know about anonymizing data and the techniques for mitigating privacy risks.

Quickly and safely aggregate geolocation data for location density analysis using a hexagonal grid system.

Test data generation is the process of creating new data that replicates an original dataset. Here’s how developers and data engineers use it.

Start building with synthetic data in just 3 lines of code 🚀

Here's how a hospital uses Gretel to help forecast staffing and resource needs for their emergency care unit, and to identify emerging trends in outbreaks.