innovation on confidential data

Build machine learning models and data pipelines without compromising privacy

Pryml is a secure way to deploy applications
to production

Banking and finance

Banks and financial institutions are highly regulated environments in which maintaining ownership of the data to be analyzed is essential to the business. Pryml allows machine learning on data that you will always own.

Private analytics for healthcare

In fields like healthcare and pharma, analytics is a more and more prominent activity where big data carries industrial secrets and sensitive information. With Pryml your industry moves, but your data doesn’t.
Data stays the way it was always meant to be: private.

Insights from private data

Organizations that outsource analytics for their business challenges run a high risk of disclosing data that is meant to stay private.
Encryption and obfuscation are not always practical solutions for computationally complex tasks like training machine learning models


Data that cannot be published usually hold essential signals for a particular business case. Providing a synthetic version of such signals represents the first step of the pryml approach to private information


Private data sources can be queried, searched and collected as long as regulations and protocols are not violated


Data scientists and engineers can securely deploy their pipelines as long as they do not compromise privacy and confidentiality

With pryml data owners
can keep their data private