Privacy

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

The Gretel research team's favorite trends and takeaways from the NeurlPS 35th Annual Conference on Neural Information Processing Systems.

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

Create synthetic data that’s safer than ever. Our simple configuration file settings enable you to secure both your data and model from adversarial attacks.

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.

Learn more about how Gretel's REST APIs automatically build a metastore that makes it easy to understand what is inside of your data.

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.

Create differentially private, synthetic versions of datasets and meet compliance requirements to keep sensitive data within your approved environment.

What if we could ensure that personal data was protected, benefiting not just the individual but also giving developers faster, worry-free access to data?

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