Gretel Blog

Run privacy engineering workloads at the touch of an API call.

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

I joined Gretel because of the opportunity, people, and problem.

In this post, we will dive into what privacy engineering is, why it’s important, and some of the core use cases we are seeing that are enabled by privacy.

Pandas provides so many options of reading data into a DataFrame, here's our short guide to ones that we found most useful.

Our new configuration templates will help you pick some of the right parameters needed to train your synthetic data models.

Implementing a practical attack to measure un-intended memorization in synthetic data models.

A game-changing AI that will disrupt the cocktail industry and spin the world on its head.

Anonymize data at access time with Gretel and Amazon S3 Object Lambda.

Gretel’s new synthetic report is here, featuring a high-level score and metrics to help you assess the quality of your synthetic data.

Here's what we learned about privacy engineering from 50+ companies and hundreds of developers.

A step-by-step guide to creating high quality synthetic time-series datasets with Python.