Check out our Github for research, source code, and examples including our core synthetic data generation library.
gretelai / gretel-synthetics

Synthetics use cases

Improve limited datasets with synthetic data

Use synthetic data to augment data sources, improve accuracy, and reduce bias in machine learning models.

Create synthetic data with privacy guarantees

Create and share realistic synthetic data freely across teams and organizations with differential privacy guarantees

Train machine learning models

Generate synthetic data to augment your datasets. This can help you create AI and ML models that perform and generalize better, while reducing algorithmic bias.

Seamlessly share data

No need to snapshot production databases to share with your team. Define transformations to your data with software, and invite team members to subscribe to data feeds in real-time

Privacy, applied

Apply state of the art NLP processing to label personal data and PII in your data streams. Stay compliant by encrypting records containing unexpected PII in real-time.

Thank you!

We are so excited to be launching soon! We will send you an email when our public beta is ready.
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