Privacy

Gretel Navigator’s synthetic data generation outperformed OpenAI's GPT-4 by 25.6%, surpassed Llama3-70b by 48.1%, and exceeded human expert-curated data by 73.6%.

Synthetic data is algorithmically generated data that mirrors the statistical properties of the dataset it’s based on. Learn how to make high-quality synthetic data.

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

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

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

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

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

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.