Unlock AI/ML collaborative models between organizations without compromising privacy as data is not shared.

Open ways of collaboration for complementary organizations but also for competitive organizations as data is not shared. This creates unimagined scenarios and has the potential to massively impact financially or operationally.

Ground-breaking collaboration scenarios between public and private organizations.

different scenarios with in the center


The traditional way of training ML/AI models is no longer valid.

Organizations must now adapt to the new standards of privacy and regulations; and will have to adopt new Privacy Enhancing Technologies (PETs) to be compliant.

Regulatory compliance diminishes execution risk, accelerates time to market, and reduces investment needs as deployment doesn’t require additional infrastructure.


Digital Ethics: Federated Learning goes beyond the principles of data ethics as it allows to extract all the benefits of data, preserving privacy as data is not shared.

Reduction of carbon footprint: Federated Learning decentralizes data processing which reduces carbon footprint.


Federated Learning addresses other challenges like Bandwidth Limitation, in situations of unreliable connectivity (i.e. offshore facilities, remote locations) as well as Excess Latency or Network Congestions.

use cases


We are currently testing our platform with top-tier global organizations with outstanding results that we will be able to showcase very soon.

Stay tuned’s PRIVACY-PRESERVING Artificial Intelligence
Against COVID-19

The critical problem that all countries face is tackling the peak of infections and avoiding the saturation of Intensive Care Units (ICUs). In order to have the necessary resources prepared at all times, has helped the Basque Department of Health to develop a platform that predicts the future needs of ICUs and adapts to different scenarios.

The platform has had a huge impact and success, allowing to predict with high accuracy:

  • Health Services’ needs, with a 7-day forecast of ICUs’ needs, along with a confidence interval
  • Where new outbreaks will occur
  • Patterns and trends in the spread of the virus and infection rates by area

This tool is also able to recognize patterns and trends in the virus, as well as identify data that is vitally important to health services, like trends in infection rates and future outbreaks, among other functionalities. The platform uses Machine Learning algorithms, along with others, in order to make predictions.
prediction of the impact of covid19 on the bac and osakidetza health centers with the help of

Compliance platforms ensures compliance with all applicable regulation.

logo of general data protection regulation

Pribatutasuna, datuen pribatutasuna funtsezko balio etikoa da.

Hori dela eta, gure plataformak Datuen Babeserako (DBEO) egungo araudi guztiak betetzen ditu, eta bat dator Europar Batasuneko Adimen Artifizialaren erregulazioari buruzko araudi berriaren zirriborroarekin.

small logo of cogx 2021 winner
small logo of cogx 2021 finalist
united registrar of systems iso 27001 and ukas management systems logos


Informazioaren segurtasuna erabateko lehentasuna da

Gure ustez, segurtasunak kalitate-estandarrak bete behar ditu, baita horri buruzko araudi osoa ere. Horregatik, datuen segurtasunaren ISO-27.001 estandarrean ziurtatuta gaude, eta gure plataformak CogX2021 sariak jaso ditu, erregulazio teknologikorako egindako ekarpen bikainagatik eta pribatutasunerako eta datuak babesteko soluzio onena izateagatik.


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