Powering your infrastructure with federated machine learning and analytics

Build your machine learning applications on a federated data infrastructure. Operationalize machine learning and advanced analytics across organizational and geographical boundaries.

Trusted by our customers & partners

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We built a federated ML platform so you don't have to

Our federated machine learning and analytics platform allows you to work with federated data, including highly sensitive data. Because data doesn't need to move, we enable you to create your own network of trusted data partners across organizational and geographical boundaries.

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Data doesn't need to move protecting IP, ensuring data privacy, and eliminating the costs of copying or centralizing data.


Works with existing tools and workflows allowing you to leverage existing data applications and model IP.


Reliable, always-on automation for training models and building data applications across organizations, geographies, or use cases.

Full AI lifecycle

Supports the data and ML lifecycle, including preferred tools, languages, and infrastructure to reduce set-up costs and time to value.

Develop with the libraries you know and love

The Apheris SDK allows you to leverage a variety of machine learning tools, frameworks and libraries. Bring your existing data pipelines and models (incl. pre-trained models) and run them with simple glue code in the Apheris platform. The SDK preserves your existing code and repo structure, so that you can easily version control the glue code file(s) together with your existing code using git

The Apheris SDK includes dedicated ML and data science modules, for privacy preserving statistics or privacy preserving ML for example, and empowers you to do foundation model fine-tuning and more.

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Computations within a single organization and across multiple parties are supported:

  • Federated analytics, from simple statistics to your custom advanced analytics pipelines.
  • Federated learning, from simple ML, such as linear models or decision trees, to advanced Deep Neural Networks.
  • Define your federation workflow and automate it - sequential, parallel, cyclic, clustered or custom federation flows - including your own aggregation functions.
  • Federated computations can be aggregated via Apheris-provided functions or user-defined functions.
  • Model validation across a single or multiple datasets. Easily compare the quality of local vs. global models.

Apheris SDK – Python library can be installed on your local computer

With the SDK, you can leverage MLOps functionality:

  • Interface with MLOps libraries like mlflow for model management and model registry.
  • Automate your federated workflows and re-run model training from your preferred job scheduler.

Private and secure

Our federated infrastructure is built with data privacy and security being central to its design. Asset policies, privacy controls, and data protection measures ensure sensitive data stays private, IP is protected, and compliance requirements are fulfilled.

Horizontal and vertical data partitioning.


Data custodians define who can do what with data. Logging of operations provides traceability for oversight and to meet audit and compliance needs.

Addressing today's challenges while unlocking value in data

Leverage existing model IP

Bring existing data pipelines and model IP and run against additional, federated datasets

Build new data or ML-enabled products

Access additional datasets to build new products or customize foundational models, for example.

Reduce risk and cost

By not needing to move data, you're reducing risk and removing the costs associated with centralizing or sharing data.

Remain compliant

Data remains with the data custodian and asset policies determine who has access to what. With all operations logged, you'll have what you need to meet compliance and audit needs.

Working across organizational boundaries


"With Apheris we found the perfect partner for exploring privacy preserving data analytics and optimization along the value chain with our customers."

Christian Winkler, Director Global Infinergy Operations BASF

Any data, any size, anywhere

Want to know more about how you can benefit from the Apheris federated machine learning and analytics platform?

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E-book - Federated Data Ecosystems in Pharma & Healthcare

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