Gretel announced the general availability of its privacy engineering APIs and services. Gretel’s comprehensive offering enables users to classify, transform and generate the industry's highest-quality synthetic data. Combined, these capabilities remove privacy bottlenecks for a myriad of development and workflow processes that prevent data sharing and stifle innovation.
A free plan for developers is available to anyone who wants to get started, and usage-based options are available for larger projects and teams.Gretel has tested its products in an open beta program for over a year, and incorporated improvements to its toolkit based on feedback from more than 60 enterprise engagements, its community of thousands of users, and open source users who have downloaded their SDK over 70,000 times.
“We’ve built a privacy toolkit that’s accessible to all developers, and scalable to any enterprise-ready project. With Gretel, anyone can classify, anonymize, and synthesize data that’s privacy-proven and highly accurate in just a few clicks, Gretel’s advanced privacy guarantees also give users complete control to adjust data privacy levels, based on their project needs, and guard synthetic data against adversarial attacks.”
-Gretel CEO and co-founder Ali Golshan.
Today, working with data is… hard. Gretel is making it easier. By building flexible, secure, and easy to deploy tools to support data-driven developers, Gretel will open a world of progress across industries, said Max Wessel, Executive Vice President & Chief Learning Officer at SAP.
Gretel has been working with teams and organizations across industries including healthcare, life sciences, finance, and gaming. Some of their recent work includes creating synthetic genomic data and synthetic time-series banking data. The broad interest in Gretel’s privacy engineering tools is not a surprising trend and is supported by analysts’ forecasts that by 2030, synthetic data will completely overshadow real data in AI models.
Gretel is committed to fostering a culture of trust, transparency, and shared knowledge with the public and developer community. They continue to open source their core synthetic data technology and research as well as offer free access to its tools through its Developer tier.
Advanced Privacy Engineering Made Accessible
With Gretel’s all-in-one privacy stack, developers everywhere can streamline workflows, and access advanced privacy engineering tools to easily
Create highly accurate, privacy-proven synthetic data
Seed pre-production systems with safe, statistically accurate datasets
Identify and remove sensitive data to reduce PII-related risks
Augment and de-bias datasets to train ML/AI models fairly
Anonymize sensitive data in real time, for data at scale
“Asking data-driven developers to exchange real-world data for synthetics requires they not only have a deep dedication to privacy, but also access to simple, intuitive solutions that return value immediately. Gretel provides all of the above and helps simplify privacy engineering,”
-Chris Hymes, the VP of Information Security, Data Privacy and Enterprise IT at Riot Games.
Gretel is also previewing its AWS S3 connector for its toolkit, and anyone interested in it can contact Gretel directly. For more information about Gretel’s toolkit, see their product overview or visit http://gretel.ai.
Gretel pioneered Privacy Engineering as a Service and a comprehensive toolkit for generating high-quality synthetic data. Their platform offers easy-to-use APIs, an open-source AI-based core that’s available for free to all developers and individuals getting started, and flexible pay-as-you-go options for production-ready projects as they scale. Gretel’s services can be used through its SaaS cloud offering or CLI for local environments.Gretel is hiring for positions throughout the company. Check out their careers page for a full list of job openings.