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Synthetics
Generate unlimited synthesized datasets.
Transform
Perform privacy-preserving transformations on sensitive data.
Classify
Identify PII with advanced NLP detection.
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Product
Gretel's Platform
Gretel’s platform includes Synthetics, Transform, and Classify APIs to provide you with a complete set of tools to create safe data.
Synthetics
Generate unlimited synthesized datasets.
Transform
Perform privacy-preserving transformations on sensitive data.
Classify
Identify PII with advanced NLP detection.
Developers
Documentation
Get started creating safe data by reading our docs.
Install the gretel-client CLI tool.
Gretel CLI
REST API reference
Build your own workflows with Gretel's REST API.
Synthetic Data Community
Join our Discord to connect with the Gretel team and engage with our community.
GitHub
View our open source projects and SDKs on GitHub.
Getting started
Environment Setup
Architecture and Components
Configure your model
Tutorials
Create Synthetic Data
Balance a Dataset
Redact Sensitive Data
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Anonymize tabular data to meet GDPR privacy requirements
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Synthetic Image Models for Smart Agriculture
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FAQs
Gretel-synthetics
Gretel Synthetics FAQs
What is synthetic data?
How does Gretel Synthetics create artificial data?
Is there an architecture diagram?
What kinds of data can I send to Gretel Synthetics?
What are the outputs from Gretel Synthetics?
Can I run Gretel Synthetics on premises?
What are gretel-synthetics premium features?
Do I still need to de-identify sensitive data when using gretel-synthetics?
What kinds of privacy protections can Gretel Synthetics help with?
How is Gretel-synthetics differential privacy different from traditional implementations?
How is synthetic data different from the original source data it was trained on?
How many lines of input data do I need to train a synthetic model?
How many columns of training data can I have?
How many epochs should I train my model with?
Does training a synthetic model require a GPU?
What is differential privacy?
How does Gretel-synthetics leverage differential privacy?
How does Gretel-synthetics implement differential privacy?
If my model trained in batches using differential privacy, what is my final epsilon (privacy guarantee)?
What are good epsilon (ε) and delta (δ) values in differential privacy?
How is Stochastic Gradient Descent (SGD) modified to be differentially private?
What does RDP order mean?