‍Gretel today announced that it has successfully achieved Google Cloud Ready - BigQuery designation, meeting a core set of functional and interoperability requirements when integrating with BigQuery. 

Following this designation, Gretel and Google Cloud will collaborate on a native integration to make Gretel synthetic data available to Google Cloud customers within the BigQuery console. Developers using Python will be able to access Gretel via DataFrames to quickly generate synthetic versions of their proprietary data and accelerate their AI projects. The new integration enables any enterprise to create, evaluate, and apply privacy-preserving synthetic data––extending the privacy and protections available within BigQuery.

"Synthetic data is revolutionizing AI development by enabling developers to rapidly experiment and iterate on data at an unprecedented speed, without the privacy risks associated with real data," said Ali Golshan, CEO and cofounder at Gretel. "By transforming raw data into valuable assets, synthetic data empowers businesses to operationalize their data more effectively and accelerate the development of innovative AI solutions. Our integration brings the power of synthetic data generation directly into BigQuery, allowing developers to leverage the speed, scale, and simplicity of BigQuery to access and leverage synthetic data across their AI initiatives." 

Access via the BigQuery console makes it simple for developers to send tables and query results directly to Gretel for fine-tuning and synthetic data generation. From there, synthetic data is conveniently loaded back into the BigQuery table automatically. Meanwhile, Clean Rooms subscribers will also be able to use Gretel to create synthetic data samples for testing prior to purchase. 

“Building the next generation of enterprise AI will require the ability for customers to safely leverage all of their data,” said Gerrit Kazmaier, VP and GM, Data & Analytics at Google Cloud. “This partnership will enable customers to utilize Gretel to generate anonymized and safe synthetic datasets that can support AI model development and testing, and accelerate AI driven transformations.”

Gretel empowers enterprises with high-quality synthetic datasets for use in analytics and AI model training. It is the only synthetic data platform equipped to meet the necessary privacy and accuracy demands of enterprise AI. The result is a new paradigm where enterprises’ entire corpus of data can be used without compromising privacy. 

Google Cloud customers interested in trialing Gretel can log onto the Gretel console. To learn more about Gretel’s upcoming BigQuery integration, visit https://gretel.ai/partnerships/gretel-plus-google-cloud. 

About Gretel

Gretel is a multimodal synthetic data platform for enterprise developers, fueled by advanced generative AI models and privacy-enhancing technologies. Users can generate a diverse array of synthetic data types, including text, relational tables, time series, and images. With customizable privacy and accuracy settings, Gretel empowers users to create secure, statistically accurate replicas of sensitive data, ideal for safe model training and data sharing. The platform also facilitates on-demand data generation to enrich limited machine learning training datasets. Serving a wide range of clients—from top financial institutions, healthcare and life sciences companies, to government and public sector organizations, as well as leading tech brands and startups—Gretel adheres to key privacy regulations such as GDPR, CCPA, and HIPAA. It's the go-to solution for organizations seeking fast, secure, data-driven decision-making, and responsible AI development. Learn more at https://gretel.ai/.