We let companies share confidential data

Our platform enables data owners to share without disclosure 

What We Do

Pryml is a secure way to share confidential data and deploy applications built on that data

Pryml target

Organisations that outsource analytics run a high risk of confidential data breaches.
Encryption and obfuscation are not practical solutions

Pryml enable

  • Secure data access
  • Synthetic data library
  • Safe-deployment to production

Pryml resolve

Pryml addresses issues around trust and security for enterprises dealing with confidential data. 

This in turn increases speed and reduces the costs of any application deployment

How we do it



The first step towards sharing confidential data is to generate a synthetic version of it



Private synthetic data is organised in libraries and made available via the data hub, a searchable and indexable component where data can be queried



Pryml securely deploys third-party applications to production

One platform across industries​


Financial institutions operate in highly regulated environments, where maintaining ownership of the data is essential to the business. Data leaks and breaches carry significant operational and reputational risks.

Generating synthetic data via Pryml offers a bullet proof solution to stay compliant with regulations yet exceed competition in the build out of innovative business solutions.


Insurance firms have heavy reliance on risk management and predictive analytics. The models used by industry leaders are all data driven.

Pryml enables secure data sharing and gives insurers access to smart data, corrected for bias, in order to increase predictive modelling accuracy.


Telco enterprises are increasingly seen as data powerhouses. The pressure is on to process increased amount of data that is coming with 5G in order to produce meaningful customer insights-like applications.

Pryml synthetic data generator is supporting Telco from secure testing environments to data monetisation marketplaces.


For years healthcare providers have been looking to improve care quality and reduce costs using data. The subject of data confidentiality is of utmost importance when it comes to HealthCare.

Analytics run on synthetic data gives HealthCare entities peace of mind that patient data will never be inappropriately disclosed.


In Pharmaceuticals, analytics is a more and more prominent activity where big data carries industrial secrets and sensitive information.

Pryml enables pharmaceuticals to build predictive models for drug recommendations in RWE (Real World Evidence) context.

With pryml data owners
can keep their data private

From Our Blog

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on the future of confidential data technology and innovation.

On the dangers of sharing data

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Are anonymous data really anonymous

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The need for provenance in machine learnin

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