Privacy Engineering as a Service for Data Engineers, Scientists, Researchers
Get started for free
Discover. Transform. Share.
Gretel use cases
Improve limited datasets with synthetic data
Use synthetic data to augment data sources, improve accuracy, and reduce bias in machine learning models.Read the post
Create synthetic data with privacy guarantees
Create and share realistic synthetic data freely across teams and organizations with differential privacy guarantees.Read the post
Power testing environments with anonymized data
Create real-time transformations to power development, test, and staging pipelines with all of the dynamism of real data.Explore transformers
Accelerate your work with data
Gretel APIs grant immediate access to creating anonymized or synthetic datasets so you can work safely with data while preserving privacy.
Train machine learning models on your dataset and generate synthetic data that is statistically equivalent.
- AI-based and open source.
- Differential privacy enabled.
- Generate unlimited data.
Automatically label data and perform privacy preserving transformations on a dataset.
- Encrypt or replace sensitive data.
- Anonymize data in real-time.
Explore records, labels and fields from any CSV.
- Stream data via our API or SDKs.
- Explore records, labels and fields.
- Create and share datasets.