Privacy engineering-as-a-service startup Gretel Labs offers a data categorization and identification platform designed to test anonymized versions of a data set automatically. The platform enables developers to synthesize, transform and classify data with an easy-to-use suite of tools and application programming interfaces that eliminate data privacy issues through safe data sharing. Gretel says its platform allows developers and data practitioners to implement intelligent, high-quality data privacy measures so they can quickly and safely innovate with data. The service is claimed to do so at a fraction of the time, cost and risk to their users’ privacy and brand. Under the hood, the platform users artificial intelligence and machine learning techniques to provide accurate, private and high-quality synthetic data with significant time savings for engineers. Machine learning is used to categorize data across names, addresses and other customer identifiers and features automatic data labeling, power testing and synthetics with support for experimentation, collaboration and building with customer data.