Gretel Blog

Learn about new features in Gretel, and how those features enabled us to discover personally identifiable information (PII) in a popular Kaggle dataset.

Gretel Outpost is a free integration architecture that automates the steps that a security team would take in assessing the risk or exposure to data.

Explore how to create a batch interface with the latest version of Gretel Synthetics on Google Colaboratory.

Look at how FastText word embeddings can help to quickly understand new datasets, and build more consistent labels for your own data.

We decided to examine the privacy preserving capabilities of the Contact Tracing proposal, how it would be implemented, and what privacy concerns exist.

Take a deep dive on training Gretel’s open-source, synthetic data library to generate electronic health records that protect individual privacy (PII).

Use Gretel Synthetics and Colaboratory’s free GPUs to train a model to automatically generate fake, anonymized data with differential privacy guarantees.

We’re going to train and build our synthetic dataset off of a real-time public feed of e-bike ride-share data called the GBFS (General Bike-share Feed)

At Gretel, we realized that we can apply machine learning, synthetic data, and formal reasoning to offer provable privacy guarantees for data.