Choose Your Model
Find out which of Gretel's APIs and models best fit your use cases with data.
When creating a new Gretel model, the type of model you create depends on your use case. This post will discuss a few primary use cases and help you identify which API best suits your needs.

I want to:

Create synthetic data with privacy guarantees API: SYNTHETICS

Create models and share unlimited amounts of realistic synthetic data freely across teams and organizations with differential privacy guarantees. Read about synthetics model configurations.

Power my testing or staging environment API: TRANSFORMS

Create real-time transformations to anonymize and power development, test, and staging pipelines with all of the dynamism of real data. Read about transform model configurations.

Detect sensitive data API: CLASSIFY

Detect sensitive information in data tables, warehouses, and log streams. Extend 40+ managed detections by authoring your own entity detections with regular expressions, all defined from a simple YAML configuration policy. Read about classify model configurations.

Improve limited datasets API: SYNTHETICS

Use synthetic data to augment data sources, improve accuracy, and reduce bias in machine learning models. Read about synthetics model configurations.
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I want to: