Because privacy matters

Protecting the privacy of personal and sensitive data is the most delicate topic for many AI engineers. XAIN provides a Federated Learning platform, so your machine learning pipeline becomes automatically compliant in privacy regulations. No more anonymization needed, no more risks of data consolidation.

XAIN introduction

Federated Learning

The privacy preserving way

Our platform leverages Federated Learning, the innovative approach of training data decentralized and efficient. This makes machine learning compliant to privacy regulations, such as EU-GDPR and CCPA. Find out how this technology works and why it makes complicated and costly anonymization obsolete.

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Federeted Machine Learning

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Case Study

The first AI application powered by XAINs FedML technology

ANDY is the first application running its training models on the eXpandable AI Network.

The solution for automated invoice processing consolidates machine learning knowledge from various data silos while keeping data privately in the respective corporate environments.

Find out more about Andy
ANDY - automated invoice processing

How it works?

AI Training

AI Training

All customers receive an individual training based on the global model and firm specifications.

Each single model is trained on the individual customer premise. No data needs to be uploaded onto our platform.

Model Optimization

Model Optimization

The training outcome is an initial learning based on the customer’s own data.

This knowledge is then being consolidated in a global training model where the model is optimized through a weighted average. No link can be drawn to the data used.



The model optimum is then distributed to the customers' applications to update and improve each individual model based on the collective knowledge acquired.

Thus, companies are able to train well performing machine learning models - even with less training data available!

We are proud to have already successfully worked with:

AWSDaimlerDeutsche BahnInfineonnVidiaOraclePorscheSAPSiemens

Get in touch

Interested in more information about XAIN, insights about Federated Machine Learning or you want to work with us?