Scaleout Systems delivers GDPR-secure machine learning with Safespring

Andreas Hellander, one of the founders of Scaleout Systems, emphasizes that the shared value of data security and the use of open source have been a strong foundation in the collaboration with Safespring.

Interest and demand for machine learning and AI have exploded recently. At the same time, a discussion is ongoing about transparency regarding the data the models are trained on and what one discloses when using the services.

Is it possible to use if GDPR compliance is to be maintained? Scaleout Systems, with their Scaleout Studio, in combination with Safespring’s infrastructure, makes it possible for companies to start with AI securely.

Andreas Hellander is one of the five founders of Scaleout Systems. Here, he talks more about the collaboration with Safespring.

Federated machine learning that meets data protection requirements

The demand for Scaleout’s solutions continues to increase. The company develops the ML platform Scaleout Studio, making tools available for machine learning. A unique functionality is that the Studio offers enhanced data security and improved privacy levels through federated machine learning. The result is the ability to collaborate on AI without risking exposure of private or sensitive data. This is particularly important in a time when regulatory requirements, such as GDPR, impose high data protection standards. Therefore, they have chosen to collaborate with Safespring. Andreas explains:

- The collaboration with Safespring works very well. By combining privacy-enhancing technologies and secure cloud infrastructure, we deliver smart solutions to our customers, who in turn use the platform to develop AI solutions in areas such as preventive maintenance, fraud detection, and energy optimization in vehicle fleets.

Andreas Hellander, CEO of Scaleout

Shared values are a strong foundation in the collaboration

Safespring’s focus on data security plays a central role in the partnership as Scaleout Systems values a secure and reliable cloud infrastructure. Operating internationally and also against other providers, they see significant benefits in a Swedish public cloud platform - so much that they now run both their own development and production on Safespring.

Additionally, there are shared values that strengthen the understanding between the companies. Both companies use open source and share the vision of a more local, collaborative, and secure cloud environment.

- Safespring is a cultural match for us, and is also a good sparring partner when it comes to developing new innovative solutions, says Andreas. Our collaboration has made Scaleout’s machine learning solutions now available as a service in Safespring’s cloud infrastructure.

Andreas Hellander, CEO of Scaleout

Large amounts of data impose high storage requirements

Since machine learning requires large amounts of data to train and develop models, Scaleout Systems has high requirements for Safespring. Scalability, data storage availability, and computational power are crucial factors.

The question of digital sovereignty also plays a role in the choice of data center and cloud service provider. Andreas explains:

- As machine learning and AI initiatives of this kind require the management of large amounts of sensitive data, it's important that companies have control and can rely on a trustworthy provider with high data security and integrity.

Andreas Hellander, CEO of Scaleout

3 tips from Andreas to those considering Swedish cloud

1. Have shared values

In a collaboration where you share the same basic ideas about software development ideology, you can inspire each other to develop in the right direction.

2. Choose a provider with open source

You will have access to a flexible, transparent, and adaptable infrastructure. Moreover, it’s easier to continue working and make continuous improvements rather than being tied to the provider’s development.

3. Avoid potential lock-in effects

Overuse of services and APIs specific to a provider can lead to lock-in effects. As can “hidden” costs such as egress costs. Today, all prerequisites exist to work “cloud-native” in a way that gives you flexibility and thus avoids lock-ins. This is especially important when working with new technology like machine learning where tools develop quickly.

Do you also want a secure and long-term partner for your data storage?

It should be easy for you to manage large amounts of data efficiently and securely. Therefore, Safespring has made sure to easily compile common questions about IT security and compliance. And if you want recommendations specific to your business, get in touch!

Petter Hylin

I am the sales manager for Safespring in Sweden and will gladly help you get started.

Call +46 (0)73 533 65 21 petter.hylin@safespring.com