Gretel Blog

Gretel Workflows orchestrate synthetic data generation, ensuring users have accurate, up-to-date data for software development, analytics, and ML/AI.

How combining agent-based methods, LLMs, and synthetic data enables natural language queries for databases and data warehouses, sans SQL.

Let’s fine tune and prompt a large language model to swap the sentiment of product reviews!

Generate private and shareable data automatically by triggering Gretel jobs in Amazon SageMaker

Learn to prepare tabular data for AI and ML with an end-to-end data cleaning workflow.

Here's how a hospital uses Gretel to help forecast staffing and resource needs for their emergency care unit, and to identify emerging trends in outbreaks.

We anonymized a massive 7 terabytes of data in a hybrid cloud environment with Gretel Transform. Here's how we did it.

Use Gretel’s text metrics to evaluate the semantic and structural similarity between AI-generated text and training text

Gretel’s suite of privacy-enhancing tools and generative AI models are now available on Google Cloud Marketplace.

Learn how to fine-tune and prompt mpt-7b to generate responses matching popular Twitter personalities with Gretel GPT.

Announcing the availability of Gretel’s high quality synthetic data generation tools in the AWS Marketplace.

Gretel GPT supports new, state-of-the-art LLMs, and makes it easier for you to trust the privacy and accuracy of LLMs for enterprise use-cases.