Data science & personal analytics

Explore the frontier in understanding your users, customers, patients, citizens - all while respecting their privacy and control over their data

"We have been very impressed by both the quality and quantity of data from a single individual to be studied for market research using digi.me. Our biggest challenge has been how to prioritise all of the opportunities."

Harun Šmrković, Chief Technology Officer, UBDI
Happy Not Happy app

Are you ready for Big Data for a single person?

Everyone knows good data beats good algorithms. What happens when you combine the best of both in a single, private, secure app? Meet the digi.me Private Sharing platform.

Digi.me enables individuals to aggregate data from across their lives and share it privately with apps after it is structured and normalised inside their digi.me Private Sharing app (we do not touch, hold or see their data). A single user can literally bring tens of thousands of rich, accurate, longitudinal data points from their social, financial, wearable, health, entertainment and music accounts for you to analyse.

The Happy, Not Happy app uses digi.me Private Sharing to bring personal data to the device and CoreML with an open source machine learning data set for sentiment analysis. With a single swipe, a user can share thousands of social posts with the app to understand sentiment month by month or post by post. In the case of this app, the data does not leave the device during the analysis, so it is 100% private and edge-based. Developers can also request that data is shared off-device, the Private Sharing contract also allows users to consent to share more data. With these options the possibilities are limitless.