Synthetic Data
for Data Sharing

Explore how to eliminate data sharing challenges that you
will face when sharing original data

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Health Plus Ai
KPN
Philips
Nederlandse Spoorwegen
Cedars Sinai
New compliance
SAS
Universiteit Leiden
Lifelines
Centraal Bureau voor de Statistiek
Euris Group
KVK
Leiden University Medical Center
UMCG

Core Value Proposition

Deliver software solutions easier, faster, and with higher quality with representative
synthetic test data

Release faster and shorten<br>the time-to-market
Release faster and shorten
the time-to-market

Synthetic data accelerates test and development cycles allowing for a shorter time-to-market.

Share the data with different parties
Share the data with different parties

Securely share data across teams or partners while maintaining compliance with privacy regulations.

Faster innovation
Faster innovation

Enable rapid innovation by eliminating delays in data access and usage for new projects.

Increase customer retention and acquisition
Increase customer retention and acquisition

Enhance customer trust and engagement with privacy-safe data sharing that drives personalized solutions.

Data Sharing Challenges

Sharing sensitive data while maintaining compliance and security can be slow and restrictive.

Privacy and Security
  • Privacy regulations like the GDPR are strict and limit data sharing
  • Lack of smart solutions to share data in a secure way
Complex governance
  • Limited knowledge on solutions
  • Trapped in a lot of bureaucracy and paperwork, causing dependencies and “legacy-by-design”
  • You will be confronted with a lot of bureaucracy and paperwork, causing dependencies and “legacy-by-design”
Getting access to data takes ages
  • Without (timely access to) data, data driven innovation and analytics is not possible
  • You miss valuable data-opportunities and momentum due to “locked” data
  • Data is critical to be smarter than the competition

Share data in a synthetic form

Our solution

Share synthetic data as alternative for sharing real data. This allows our customers to eliminate those aforementioned data-sharing challenges. Ultimately, this creates a strong foundation for data-driven innovation, enabling agile access and free data sharing.

Two formats for data-sharing solutions in practice:

Ad hoc synthetic data
Ad hoc synthetic data

We see ad-hoc data synthetization when agility in data sharing is desirable. As alternatively to realizing data-driven innovation with real (sensitive) data, here one can realize data-driven innovation on synthetic data. This situation will boost agility by avoiding the data sharing hurdles one would normally face.

Setup a synthetic data warehouse
Setup a synthetic data warehouse

Many organizations have a data warehouse containing original (sensitive) data. Our suggestion would be to introduce a data warehouse with synthetic data next to the data warehouse with original data. Now, your employees (or even 3th parties) can easily access and share synthetic data from the synthetic data warehouse to realize data-driven innovation upon and will not face those data access hurdles.

Use cases

Product Demo
Product Demo

Your demo data may be suboptimal, leading to missed opportunities during product demonstrations.
Synthetic Data in Healthcare
Synthetic Data in Healthcare

Explore the value of synthetic data in healthcare
Synthetic Data for Test Data
Synthetic Data for Test Data

Using personal or production data as test data is not allowed
Fast Data Sharing
Fast Data Sharing

Explore how to eliminate data sharing challenges that you will face when sharing original data
Advanced Analytics
Advanced Analytics

Build strong data foundations with easy and fast access to AI generated synthetic data