VEIL. AI team members from left: Teemu Perheentupa, Robert Mills, Tuomo Pentikäinen, Mehreen Ali, Timo Miettinen and Janna Saarela
Anonymization engine up & running
At the core of VEIL.AI, we find the company’s anonymization engine: a brand new, powerful approach to de-identify personal or otherwise sensitive data.
“The anonymization engine facilitates sharing and analyzing data in low or zero-trust environments and ensures that neither anonymity nor data quality is compromised,” explains Pentikäinen.
The anonymization engine can be used at three levels: One-off anonymizations (e.g. piloting, research projects); continuous anonymization service (e.g. biobanks data access point); and as part of system architecture (e.g. anonymization competence and user interface implemented into hospital data lake).
The startup can handle several interesting data types, both in the realms of structured data and unstructured data. Under structured data, there are data types such as biobank data, registry data, clinical data and survey data. Unstructured data may be, for example, geo-location, genome or imaging data.
Synthetic data is a totally new philosophy of putting data together. In the coming years, we expect the use of synthetic data to really take off.
Health Capital Helsinki