Nationwide often need to partner with third parties to become quicker and more agile in their innovation. But validating third party vendors requires quality data. With Hazy, they generate highly realistic synthetic datasets and speed up their vendor validation.

Wells Fargo uses data to evaluate ML techniques and new software. They previously relied on datasets that were expensive and time consuming to generate. Now using synthetic data, they generate larger datasets for training and can easily dial up specific testing scenarios.

An investment manager had lengthy governance steps when provisioning data to internal teams and third parties. What was supposed to facilitate rapid product prototyping was actually a very slow process. With Hazy, data provisioning now takes days rather than months.

A Nordic bank depends on test data to build new products. Traditionally they would populate augmented production data manually – a time consuming, expensive and risky process. Now they use Hazy to generate synthetic datasets. It’s faster and always compliant.