Gretel Blog

Gretel integrates with Azure so customers can leverage their compound AI system Navigator for high quality synthetic data generation.

Validating synthetic math datasets through inter-model variability and benchmark alignment.

How synthetic data is transforming enterprise AI in 2025 by addressing privacy, fine-tuning, and scaling challenges.

Gretel releases an open synthetic dataset to align language models for safety.

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 Tabular 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.