Data Is More Valuable When It Can Be Shared

Today, we are thrilled to announce the general availability of Gretel's privacy engineering APIs and services.

Data Is More Valuable When It Can Be Shared

Since founding Gretel two years ago, we have often been asked “What is the elevator pitch for Gretel?”  Well, a Gretel customer put it best with a simple statement: “Data is more valuable when it can be shared.” 

One of the biggest bottlenecks to innovation that developers and data scientists face today is getting access to data, or creating the data that you need to test an idea or build a new feature. From our experience working at AWS, Google, OpenAI and with other leaders in the data industry, we know first hand that enabling developers to safely learn and experiment with data is the key to rapid innovation.

As developers and data scientists, we don’t always need - or even want - access to sensitive customer information. That’s where synthetic data comes in. 

What if you could get access to an artificial and privacy-preserving version of data in minutes, with 95% of the accuracy of the real world data without having to wait weeks for manual anonymization and approvals? What if you could create additional data from just a few examples without having to wait weeks or months for annotated data to be created?

Gretel can do that for you. At Gretel, we are making this possible through our state of the art synthetic data and privacy engineering tools. 

Today, we are thrilled to announce that Gretel is at General Availability (GA). For us, GA reflects the same commitment to an open-source core, continuing to learn and iterate in public, and create simple and cleanly documented APIs– now with the scale and efficiency to run as part of your data science pipelines and workflows. It’s been amazing to see what is possible with Gretel. We are building Gretel’s APIs to help developers reduce bias in ML datasets, creating realistic location data from a few samples for the metaverse, and recreating the results of life sciences experiments using synthetic genomic data

Going forward, we will continue to post research, source code, and examples about enabling data sharing and access at scale. Sign into our free tier and give Gretel a try, you can run Gretel’s APIs to Synthesize, Transform, or Classify data – no code required

For anyone interested in deploying our toolkit in production AWS environments, we’re previewing our new S3 Connector. If you’re interested or want to start a conversation, drop us an email at hi@gretel.ai. You can also visit our community Slack and start a conversation with our developers and data scientists.

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