Together we can

Train AI better

XAIN builds the technology to scale your AI training. You can train your model based on several different data sources - without having to share that data with us. Your data can stay where it is and you can build privacy-preserving AI applications.

XAIN introduction

Introducing the eXpandable AI Network

Because MANY brains are better than one!

XAIN builds technology that yields the most efficient model training available. Based on the latest research on Federated Machine Learning (FedML), any model can learn from the knowledge of the entire network. This is how we make any machine learning application scale!

Find out more about FedML
Federeted Machine Learning

Why FedML is such a good solution?

Performance

Performance

Achieve better model training - even with less data available.

Privacy

Privacy

FedML is privacy preserving - all data stays in its save environment.

Availability

Availability

No data anonymization necessary - start your project right away.

// 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.

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.

Distribution

Distribution

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!

About us

Our mission is to make AI scalable while also protecting data privacy, granting companies the ability to harness the full potential of AI in a safe and secure manner.

Milestones

Our founders

Leif-Nissen Lundbæk

Leif-Nissen Lundbæk

CEO & Co-Founder

Felix Hahmann

Felix Hahmann

Chairman of Supervisory Board & Co-Founder

Prof. Michael Huth

Prof. Michael Huth

CTO & Co-Founder

We are proud to have already successfully worked with:

AWSDaimlerDeutsche BahnInfineonnVidiaOraclePorscheSAPSiemens

Get in touch

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