Data

Gretel partners with Google Cloud to harness the power of synthetic data and accelerate safer generative AI adoption in the enterprise.

Introducing Gretel Relational, enabling organizations to generate high-quality synthetic databases while preserving cross-table relationships.

A walkthrough of our new multi-table transform and multi-table synthetics notebooks, which can be used independently or simultaneously.

Effective strategies for leveraging high-quality synthetic data to improve RAG model performance.

Leverage Gretel’s New Ultra-Fast and Fully Flexible De-Identification and Rule-Based Transformation Solution for HIPAA Compliance.

Gretel’s privacy-first generative AI is now available to all Azure users as well as select enterprises through the Microsoft for Startups Pegasus Program.

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

Augment or balance your ML datasets in minutes with state-of-the-art generative models.

Generate large volumes of tabular synthetic data at high speed.

Learn the simplest way to generate synthetic data without setting up your own infrastructure and GPUs.

Machine learning models can be trained to recognize patterns in datasets. By utilizing algorithms, they can learn to make decisions based on these patterns.

Pandas provides so many options of reading data into a DataFrame, here's our short guide to ones that we found most useful.

Learn about new features in Gretel, and how those features enabled us to discover personally identifiable information (PII) in a popular Kaggle dataset.

We founded Gretel based on our beliefs that data shouldn’t be scary.

Create differentially private, synthetic versions of datasets and meet compliance requirements to keep sensitive data within your approved environment.

Learn more about how Gretel's REST APIs automatically build a metastore that makes it easy to understand what is inside of your data.

A brief exploration of model soup, the new ensembling technique that takes the average weights of multiple models to improve overall performance.

How synthetic data can help nonprofits improve their business operations and their impact on the people they serve.

Smart-seeding lets you train a synthetic data model to auto-complete partial records and text.

Anonymize data at access time with Gretel and Amazon S3 Object Lambda.