Gretel

The future of privacy-preserving generative AI is bright. AI teams can now use Gretel with #Azure AI Foundry to design and generate secure synthetic datasets tailored to their specific business needs. This integration significantly reduces costs and time compared to traditional data labeling methods, while maintaining robust privacy and compliance standards. Enterprises are already leveraging Gretel to build specialized Small Language Models (SLMs), enhance reasoning abilities in Large Language Models (LLMs), and scale data generation from limited real-world examples. “EY is leveraging the privacy-protected synthetic data to fine-tune Azure OpenAI Service models in the financial domain," said John Thompson, Global Client Technology AI Lead at EY. "Using this technology with differential privacy guarantees, we generate highly accurate synthetic datasets—within 1% of real data accuracy—that safeguard sensitive financial information and prevent PII exposure. This approach ensures model safety through privacy attack simulations and robust data quality reporting. With this integration, we can safely fine-tune models for our specific financial use cases while upholding the highest compliance and regulatory standards.” Check out the announcement for more details: https://lnkd.in/d5CMVW3y #SyntheticData #Privacy #AI

?? Introducing Sample-to-Dataset: Gretel’s new workflow in Data Designer lets you generate large-scale, diverse synthetic datasets from just a few sample records. ?? Automatically expand the problem domain as a human expert would ?? Maintain your data's exact format, style, and logic ?? Experiment faster with preview-and-iterate workflows Imagine going from 5 sample records to 1,000 high-quality, structured records—perfect for fine-tuning AI models or balancing datasets. ?? Dive into the details: https://lnkd.in/eGqEvhfT #SyntheticData #AI #DataScience

Introducing Gretel Navigator Fine Tuning with Differential Privacy. Our model of choice for generating synthetic tabular datasets now features mathematically-proven safeguards for privacy — ideal for numerical, categorial, or even free-text columns. ?? ?? Discover how this breakthrough can help enterprises unlock sensitive datasets to surface powerful insights and trends without compromising utility: https://lnkd.in/d4MVmcVk #AI #Privacy #SyntheticData

?Our collaboration with Microsoft Azure OpenAI Service is transforming the way organizations tackle AI model development, leveraging the Gretel platform to solve data bottleneck problems. Data bottlenecks, privacy challenges, low-quality AI data, and high costs often slow down innovation in AI. Our integration with Azure empowers teams to overcome these hurdles, enabling them to generate high-quality, privacy-preserving synthetic datasets tailored to their business and customer needs. Whether it’s tabular, time-series, structured data or unstructured text, Gretel supports it—and now, fine-tuning models in Azure OpenAI Service is faster, safer, and more scalable than ever. This collaboration isn’t just about efficiency; it’s unlocking new AI use cases. From enhancing reasoning abilities in LLMs to improving SLMs at a fraction of the cost, synthetic data is proving its value across industries. Enterprises like EY are already leveraging this technology to fine-tune models in highly sensitive domains like finance, all while ensuring privacy and compliance.

Thrilled to announce that Gretel and Microsoft Azure are bringing privacy-preserving synthetic data to Azure OpenAI Services. This opens up incredible opportunities for industries like finance, healthcare, gaming, automotive, robotics, and more to innovate with AI while keeping data privacy front and center. Data privacy and regulatory hurdles have long held back organizations from fully leveraging their sensitive and proprietary data. By integrating Gretel's synthetic data platform with Azure's AI services, we're enabling teams to securely unlock insights, share information, and customize AI models without compromising on privacy. Our multi-modal platform generates high-quality synthetic data with differential privacy guarantees, supporting a wide range of data types—from text and tabular data to complex JSON structures. This collaboration isn't just about individual organizations; it's about strengthening the entire AI ecosystem. By making privacy-preserving synthetic data more accessible, we're fostering an environment where innovation can happen without the usual bottlenecks.

In yesterday's #MicrosoftIgnite keynote, Satya Nadella spotlighted Gretel’s role in advancing AI: "There is no AI without data." He emphasized how Microsoft's collaboration with Gretel "removes data bottlenecks and makes data AI-ready for training." Watch the clip: https://bit.ly/3Og5qFw Azure customers: Explore our new tutorial to customize compliant models with Gretel synthetics and Azure OpenAI Services. Learn to build a financial analyst copilot that turns regulatory filings into actionable insights: https://bit.ly/4hUG9hX #SyntheticData #Privacy #AI #Azure

Join Amazon Web Services (AWS) and Gretel for an event on boosting AI model performance with high-quality synthetic datasets. Discover how to quickly create, edit, and enhance synthetic datasets with a simple prompt, enabling you to fine-tune models while ensuring data privacy.

What if you could train a financial risk analysis copilot—without exposing sensitive data? With Gretel and Microsoft Azure OpenAI Service, it’s possible. Our privacy-preserving architecture enables financial teams to: ? Generate synthetic data with privacy guarantees ? Fine-tune AI models safely and securely ? Build tools that turn regulatory filings into actionable insights Now, financial analysts can innovate faster while staying compliant. ?? Learn more and explore the solution: https://lnkd.in/ehRBWGv7 #AI #Privacy #SyntheticData #Finance

Great to see this announcement and the work that #gretel is undertaking in partnership with #microsoft. Well done to Ali Golshan, Alexander Watson and the entire team at Gretel. Looking forward to our future and further collaborations.

?? Unlock the Power of AI Models Customization Fine-tuning is key to aligning AI Models with unique business goals—but challenges like lack of tooling, data, and expertise often get in the way. To solve this, Azure AI Foundry is teaming up with Weights & Biases, Scale AI, Gretel, and Statsig to simplify customization with advanced tools, synthetic data, expert insights and in-production experimentation. Learn more in this blog: https://lnkd.in/ga_uTXBp #MSIgnite #AI #FineTuning #AzureAI #AzureAIFoundry Yina Arenas Steve Sweetman Mads Bolaris Richard L. Tso Shilpa Dabke David Seda Rajat Gupta Felipe Benavides Sasha Manuilova Sophia Chan Ryan Hylas Elisa Garcia Anzano Alexander Watson Rebecca Kao Vijaye R. Skye Scofield