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

AWS re:Invent is less than 1?? week away! ?? Visit us at booth #1605 to meet the Gretel team and get a demo on creating high-quality synthetic datasets without compromising privacy. ?? Solve data bottlenecks in AI/ML ?? Protect privacy and preserve sensitive information ?? Explore real-world use cases and applications of synthetic data across industries We can’t wait to connect with you in Vegas! https://lnkd.in/eKyctdwE #AWSreInvent #syntheticdata #dataprivacy

And the lineup of speakers just keeps growing! ?? Join the C2C #community on 12/3 for a full day of learning and connecting with #data professionals, analysts, and enthusiasts at #2Gather Toronto. Sponsors: Google Cloud, Aiven, Tamr, and Wipro Meet the Lineup of Speakers: ?? Stephen Lee, TELUS ?? Julia Zhu, Alectra ?? Luke Mellors, CNA Insurance ?? Shannon Koeppen, Livingston International ?? Louis Anthony S., FLUIDEFI ?? Stefan Gavrilovic, Gretel #AI ?? Bonnie Donovan, #GoogleCloud ?? Ali Faiz, Rollbar ?? Mike Stone, LSEG (London Stock Exchange Group) ?? Neil Bunn, #Googler ?? Amith Mathew, #Google ?? James Arlen, #Aiven ?? Ryan Finger, #Wipro ?? Aditya Dhekney, Google Cloud Canada Register today: https://lnkd.in/gV5rptJS

Check out our latest walkthrough on Gretel's Data Privacy Score, which evaluates privacy risks for synthetic tabular data. This new scoring system simulates Membership and Attribute Inference Attacks to assess protection against real-world threats, complementing tools like Privacy Filters and Differential Privacy. Learn about the methodology, what the scores mean, and how to improve them—all while ensuring compliance with #GDPR and #CCPA. Watch now: https://lnkd.in/ecMjp-Ub #DataPrivacy #SyntheticData #Compliance

Despite the immense potential for innovation in finance, the industry often faces hurdles due to technical complexities.?That's why we're excited to share a new development at Gretel, Synthetic Text-to-Python dataset tailored specifically for FinTech. By enabling #LLMs and #SLMs to "speak finance," we're making it possible to turn plain language requests into precise, domain-specific Python code. Imagine saying, "Create a Python script to analyze transaction patterns for fraud detection," and getting usable code instantly. This enables analysts to security teams to bring their ideas to life without needing deep coding skills. Financial systems are intricate, filled with specialized terms and strict regulations. Generic datasets often miss these nuances, making it hard for AI models to produce accurate code for financial tasks. By customizing models with our FinTech-focused dataset, we're helping them understand these complexities—from secure data handling to compliance standards—so they can generate code that's both useful and safe. Using Gretel, we've crafted a high-quality synthetic dataset that reflects real-world FinTech scenarios. We've: -- Guided LLMs to act like Python experts in finance. -- Covered various sectors like banking, fraud detection, and smart contracts. -- Ensured the code is accurate and relevant through rigorous checks. By teaching AI models to understand and generate code within the financial domain, we're lowering the barriers to AI adoption in the industry. This not only speeds up innovation but also allows more people to contribute, even without extensive coding experience.

Transforming natural language into domain-specific Python code is now possible with our new synthetic Text-to-Python dataset for FinTech. Imagine asking "Create a script to analyze transaction patterns for fraud detection" and instantly getting working code. Our new dataset, created with Gretel Navigator, enables LLMs to generate precise, financial-domain code without requiring deep technical expertise. Key features: 25,000 curated records covering banking, trading, compliance & more Multiple complexity levels from beginner to expert Validated Python code with top quality scores Apache 2.0 licensed for open use Learn how we built it and create custom datasets of your own. Blog: https://bit.ly/4eOaf3X Dataset: https://bit.ly/4eMPrd5 #SyntheticData #OpenData #AI #FinTech

Excited to see Gretel recognized as part of the data transformation layer for AI-powered banking. Embedding privacy at the foundation of the stack isn’t just smart for banking—it's the way forward for every industry. #SyntheticData

Heading to re:Invent post-Thanksgiving. Booth 1605, the same year that Don Quixote was published.

At Gretel we are hiring for 15+ immediate open headcounts, across everything from Applied Science, Sales, and Marketing. At this early stage in AI, it is difficult to predict where AI will go exactly, but we can be certain it will require safe, high-quality, and domain specific data. So, come help us solve these data bottleneck problems and accelerate the whole AI ecosystem. Feel free to DM me directly if you find one of the roles a particularly good fit, or even if you don't see a specific role but interested in the problems we're solving. Better data makes better AI. *No recruiters please*

Gretel's SDK integration makes it easier to fine-tune OpenAI models on Microsoft Azure with synthetic data and built-in differential privacy. Whether you're starting with your own data or generating new datasets from prompts, this integration lets you safely work with domain-specific or sensitive data. Looking forward to seeing how teams use this to unlock new possibilities! ?? https://lnkd.in/g8FxYXYv