Gretel Blog

A new standard for ensuring regulatory compliance and managing the complexities of compound AI systems.

Use Gretel Navigator on Amazon Bedrock to create safe, scalable synthetic data for training AI to understand and execute tool commands.

Train financial LLMs with Gretel's Synthetic Text-to-Python dataset to transform natural language into precise, domain-specific Python code for FinTech.

How to measure and minimize personally identifiable information (PII) risk in synthetic data.

Learn how to generate secure, high-quality synthetic tabular data using Navigator Fine Tuning and Differential Privacy tools. 🛡️ 🚀

Seed to succeed: use the sample-to-dataset workflow to create diverse, large-scale synthetic datasets tailored to your needs with nothing but a few samples.

Leveraging Gretel's privacy-preserving synthetic data generation platform to fine-tune Azure OpenAI Service models in the financial domain.

Gretel announces Data Designer for building high-quality, custom synthetic datasets with Navigator. Improve AI models on domain specific tasks and reasoning.

Gretel fine-tuned, synthetically-enhanced GLiNER models for better PII & PHI detection—datasets included.

How to safely fine-tune LLMs on sensitive medical text for healthcare AI applications using Gretel and Amazon Bedrock

What The Recent Paper on LLM Reasoning Got Right—And What It Missed.

Gretel, a leader in privacy-preserving AI and synthetic data generation, has been named one of LinkedIn’s Top U.S. Startups