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Article
Apheris Compute Gateway - Let's collaborate.
Apheris Compute Gateway 3.0 provides an end-to-end federated analytics and machine learning solution that enables everyone to collaborate securely on highly sensitive data.
Jan Stuecke
News
Apheris Compute Gateway - Let's collaborate.
Apheris Compute Gateway 3.0 provides an end-to-end federated analytics and machine learning solution that enables everyone to collaborate securely on highly sensitive data.
Jan Stuecke
Article
Top 7 Open-Source Frameworks for Federated Learning
Open-source frameworks for federated learning are a great way of getting first hands-on experience. Here are our Top 7 with their respective pro and cons
Marie Roehm
Article
Achieving Data Privacy in ML/AI
In this article, we explore Privacy Enhancing Technologies (PETs) and highlight their need in the context of ML/AI projects that use sensitive or regulated data. We start by demystifying PETs and providing concrete examples to help CTOs and product owners make informed decisions about how to improve data protection.
Inken Hagestedt
Article
Federated learning: from academic insights to industry applications
In December, the annual NeurIPS conference took place. With the biggest conference in machine learning research happening, I was curious to see what was going on in the world of federated learning. Here are my 5 take-away on how federated learning can be applied in industry today.
José-Tomás (JT) Prieto, PhD
Article
Pioneering new frontiers within regulatory boundaries
Computational governance enables machine learning on European healthcare data.
European hospitals face a unique challenge, balancing complex regulatory frameworks with the need to make valuable data available for reserach. Computational governance exists as a solution and enables compliant research on health data.
Jan Stuecke
News
Apheris Launches Trust Center, Elevating Security and Data Privacy Standards
The Apheris Trust Center serves as a comprehensive resource for organizations seeking to uphold the highest standards of security and data privacy. It offers guidance and our certifications and attestations, including ISO 27001 and SOC 2, that customers value as essential components to fulfil their compliance obligations.
News
Apheris Achieves SOC 2 Type I Attestation – Reinforcing Our Commitment to Security
Apheris achieves SOC 2 Type I attestation, reaffirming its commitment to data security and privacy, and the comprehensive measures we have implemented to protect sensitive information and ensure the highest level of security.
Article
Navigating the compliance maze in AI development
As AI reshapes many industries, the balance between innovation, security, and compliance has become paramount, especially in regulated sectors.
Article
Governed, secure, and private computational access to federated patient data is revolutionizing healthcare AI
MedTech AI revolution depends on computational access to fine-grained patient data to train enhanced ML models. Apheris provides governed, secure, and private computational access to data for ML, enabling fast and easy FDA approval for new MedTech data products.
Marie Roehm
Article
The EU AI Act: Understanding and Preparing for Compliance
Exploring the EU AI Act, a pivotal regulation addressing AI's multifaceted nature, this blog outlines risk levels, high-risk system requirements, and preparation for compliance. Apheris's solution for various governance, privacy, and security obligations is highlighted, emphasizing a shared commitment to responsible AI.
Robin Röhm
Article
Hey, your data is on mute
Reaching universal agreement on how to regulate AI is impossible. But a carefully designed cyclical process can lead to efficiencies in an enterprise's journey towards trustworthy, accountable, and sustainable AI. In this blog, I navigate the regulation space through the eyes of a data custodian.
José-Tomás (JT) Prieto, PhD
Article
Enlightening Dark Data
There is so much useful data around us. Yet most data is not accessible for machine learning or other large scale analytics. In this article, we will explore why this is and what needs to be in place to enlighten this dark data.
Jan Stuecke
Article
Enabling IP-Preserving Computations on Sensitive Data
Machine learning and AI needs domain-specific data to be trained for its various use cases. Often this data is sensitive and falls under various privacy regulations. In this article we will introduce the Apheris Compute Gateway as a solution for contributing sensitive data to ML projects.
Jan Stuecke
Article
The Rise of Federated Learning
Companies are benefiting from federated learning by being able to access data without the costs, privacy and IP risks associated with copying or centralizing data.
Article
Delivering maximum social benefit from artificial intelligence (AI): Leveraging its capabilities responsibly
AI safety is not a future problem to solve, it’s a real problem right now. In this blog I'll explain the challenges we face as a society in developing and using AI, and propose some operating principles to help us leverage AI for social good.
Britta Srivas
Article
We have to act now - how to take a responsible approach to sustainability as an organization
The clock is ticking. The time to act on climate change is now. In this blog, I'll take a closer look at practical thoughts on climate thinking and action in organizations.
Michael Höh (PhD)
Publication
AI regulation: Why it needs to come sooner rather than later
"As AI adoption gathers momentum, it is essential we get in front of this generational technology and regulate it in a way that works for everyone – before it is too late."
Robin Röhm
Article
The Why, When, Where and How of Federated Learning
In this blog, we'll explore how Federated Learning can solve the common challenges around data access. It’s no secret that lack of access to the right data is one of the leading causes of project failures; what is surprising is that the right data often exists in data silos that, frustratingly, data scientists cannot access.
Article
Understanding the Opportunities: Federated Learning and Consumer Data
In this blog we will explore the ways in which industries, including those reliant on consumer data, can use federated learning as an effective alternative to data sharing.
Article
Large Language Model: in Conversation with ChatGPT
In conversation with ChatGPT about the relationship between large language models (LLMs) and federated learning.
Article
Securing ML Models: Apheris' Contribution to ML Security
Together with the German Federal Office for Information Security we've developed frameworks and recommendations for ML practitioners to help secure ML models and maintain appropriate security measures.
Marie Roehm
Article
Challenges with implementing federated learning
Explore some of the common challenges organizations face when implementing federated learning and key considerations that can help them overcome those challenges and reap the rewards of working with federated data.
Article
Data without borders
Organizations across the globe are quickly waking up to the need for safe, hassle-free data collaboration without the limitations, barriers, and security issues associated with data sharing. Apheris' Compute Gateway is making secure data collaboration across boundaries a reality.
Article
Celebrating women's contribution to STEM fields
11 February is the International Day of Women and Girls in Science. We interview Evelyn, Data Science Experience Lead at Apheris, and give you an insight into the life of a successful woman in science.
Marie Roehm
Article
The Collaborative Potential of Federated Machine Learning
There are incredible opportunities to be seized through federated machine learning across many industries. While some early innovators have recognized the potential, many have yet to seize the opportunity before them.
Article
Unlock unprecedented collaboration potential
Following its 77th session, the UN General Assembly championed collaboration as the cement that could strengthen individuals, organizations, and industries against both current and future challenges. Read on to find out how.
Article
Refine large language models to boost AI performance
Open AI's ChatGPT is very popular, yet not ready for enterprise adoption due to accuracy, security & privacy concerns. By refining large language models this can be tackled. For organizations that operate in a regulated space, federated learning can be used to train on distributed data to unlock value while maintaining privacy.
Marie Roehm
News
Apheris achieves top information security certification, ISO 27001
Certification highlights our mission and focus on best practices for federated machine learning and analytics, enabling organizations to securely build and operationalize machine learning and data applications across boundaries.
Article
The Secret to Collaborative Data Ecosystem Success
Data is widely considered to be the lifeblood of modern organizations, but it’s only as valuable as the insights that can be mined from it. A collaborative data ecosystem helps organizations come together to mine much-needed insights.
Article
The big data opportunities: manufacturing
In order to rise above today’s challenges, manufacturers need to come together, pool their collective assets and insights, and create modern solutions to modern problems.
Article
A time to reflect and look forward
As we near the end of the year we take a look at key themes from 2022 and what to expect in 2023. Here are our top predictions for the year ahead.
Article
How data collaboration is changing the world
More businesses are waking up to the value of data and the necessity of data collaboration in harnessing its power.
Marie Roehm
Article
Data collaboration vs data sharing
It's often assumed that data sharing is required in order to derive value from data held across multiple organizations in a value chain. However, data sharing comes with challenges. Working with federated data, however, addresses these challenges and allows for better collaboration across organizational boundaries.
News
Apheris raises €8.7m to power development of smarter AI and collaboratively solve the world’s biggest challenges
Seed extension round led by Octopus Ventures to drive growth of platform enabling organizations to unlock terabytes of valuable data risk-free
News
Apheris launches platform to unlock data and enable collaboration to solve the world’s biggest problems
The Apheris Platform enables multiple organisations to extract value from each other’s decentralised data sets and overcome regulatory, technical, and commercial challenges.
Article
Apheris' first carbon removal purchases
Our focus on sustainability extends beyond the impact we have on our customers, and our environmentally conscious mindset is at the core of Apheris’ work culture.
Article
7 Myths About Federated Learning
In our daily work as a company that builds a platform for federated and privacy-preserving data science, we are often asked to clarify concepts around federated learning with customers. This article highlights 7 common myths about federated learning (FL) and, using practical examples, shows you exactly why they are misleading.
Marie Roehm
Article
How to Choose the Best Federated Learning Platform
How can you evaluate platforms around emerging technologies like federated learning? This article gives you guidance on what your selection criteria should be.
Marie Roehm
Article
The Three Adoption Stages of Privacy-enhancing Technologies (And Why We Are Stuck on Level Two)
PETs are massively changing how we operate, and how we have to think about the data and AI landscape. Introducing such a game-changer into large enterprises has to be done with the highest precision, and a lot of foresight.
Marie Roehm
News
The State of Data Collaboration – why we are asking for your help
Participate in our survey and shape the future of Data Collaboration. For a completed survey you will recieve a report that will help to benchmark yourself and your company on your collaborative ecosystem efforts.
Article
7 Value Drivers of Complementary Data - Your Path to Unlocking the Benefits of Federated Data
There is only value in data if it can be used, and if there is appropriate access to that data when it is needed. Learn how you can turn decentralized, federated data into a complementary strategic data asset.
Marie Roehm
Article
The Five Qualities of Collaborative Data Ecosystems
Over the past decade, organizations have focused heavily on implementing the culture, tools, and processes to create value from data with data science and machine learning within the enterprise. But this transformation doesn't intend to stop at corporate boundaries. Read the article to find out more
Article
What Are Collaborative Data Ecosystems?
Enterprises across industries are realizing that collaboration on data, machine learning and data science is the key to solving the biggest challenges of our time. This leads to a massive rise of collaborative data ecosystems around the globe. Read more if you want to know what collaborative data ecosystems are
Article
The Future of Data Products – 6 Industry Trends For Frontrunners
If you’ve been successful to date with building industry-leading data products, you don’t want to rest on your laurels. Instead, you should be trying to extend your lead. However, this can be daunting task in an industry that is in constant flux as the data, machine learning and AI landscape.

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