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Generate synthesized datasets.
Transform and anonymize data.
Ingest, tag, & catalog check for PII.
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An open source data transformation library and bindings to Gretel APIs
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Architecture and Components
Configure your model
Create Synthetic Data
Balance a Dataset
Redact Sensitive Data
July 13, 2021
Gretel releases Beta 2
Run privacy engineering workloads at the touch of an API call.
June 15, 2021
What's new in Beta2
Beta2 for Gretel.ai is all about delivering privacy engineering as a service through clean, simple APIs.
June 8, 2021
Why I Joined Gretel
I joined Gretel because of the opportunity, people, and problem.
June 2, 2021
What is Privacy Engineering?
In this post, we will dive into what privacy engineering is, why it’s important, and some of the core use cases we are seeing that are enabled by privacy.
May 13, 2021
A guide to load (almost) anything into a DataFrame
Pandas provides so many options of reading data into a DataFrame, here's our short guide to ones that we found most useful.
May 3, 2021
Synthetic Data Configuration Templates
Our new configuration templates will help you pick some of the right parameters needed to train your synthetic data models.
April 27, 2021
Practical Privacy with Synthetic Data
Implementing a practical attack to measure un-intended memorization in synthetic data models.
April 5, 2021
Introducing the Gretel Bartender
A game-changing AI that will disrupt the cocktail industry and spin the world on its head.
March 30, 2021
Anonymize Data with S3 Object Lambda
Anonymize data at access time with Gretel and Amazon S3 Object Lambda.
March 29, 2021
How accurate is my synthetic data?
Gretel’s new synthetic report is here, featuring a high-level score and metrics to help you assess the quality of your synthetic data.
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