Privacy-Preserving technologies adapted to your business needs

BENEFITS OF
FEDERATED LEARNING

NEW BUSINESS SCENARIOS & RESULTS
IMPROVEMENT WHILE PRESERVING
PRIVACY

Sherpa.ai’s solution sits at the intersection of results improvement, regulatory compliance and ESG standards.

Sherpa.ai unlocks the potential of data collaborations between organizations without compromising privacy as data never leaves the organization’s environment.

Data is never shared which reduces compliance burden as well as the risk of data breaches.

The platform promotes an ethical use of data, respecting privacy and contributes to the reduction of carbon footprint in model training.

different scenarios with sherpa.ai in the center

RESULTS

Massive operational and financial impact from AI model training (incluing heterogeneous data) without sharing any data.

Unlock new ways of collaborations and business scenarios between different organizations, that until now, were not able to work together.

Solve complex challenges like rare diseases, realising the full potential of data while protecting privacy as data is not shared.

CURRENT AND FUTURE REGULATORY COMPLIANCE

The traditional way of training ML/AI models is no longer valid.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

ESG & SUSTAINABILITY

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.

Federated Learning decentralizes data processing which decreases the amount of energy required for model training and reduces carbon footprint.