Share confidential data.
Keep it private.

Pryml enables organisations share their confidential data without disclosing it.

What We Do

Pryml is an enterprise-scale platform to synthesise data and deploy applications built on that data back to a production environment.

Test ideas. Launch new products. Fast. Secure.


Outsourcing analytics and sharing data leads to high risk of breaches.

Encryption and obfuscation are not practical solutions.


  • Secure Data Access
  • Synthetic Data Library
  • Safe-Deployment


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

Deployment speed is increased and costs are lowered.

the pryml approach

1. Generate

Produce a synthetic version of the private data

2. Discover

Synthetic data is organised in libraries and made available via the data hub

3. Deploy

Securely deploy 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

Share and subscribe for our blogs and articles so you wont miss any updates
on the future of confidential data technology and innovation.

On the dangers of sharing data

There are very good reasons why a financial institution should never share their data. Actually, they should never even move their data. Ever.

Are anonymous data really anonymous

Last Sunday, the Observer newspaper published a story denouncing the sale of medical data – compiled from GP surgeries and hospitals...

The need for provenance in machine learning

There is no doubt that AI — or whatever people mean when they recklessly toss around words like machine learning — will only rise in prominence in both the near — and long — term future.

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