Any data, any size, anywhere
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Power your data infrastructure with federated machine learning and analytics
Helping you to securely build and operationalize data applications and AI across organizations, industries, and borders — all while protecting privacy and IP
Trusted by our customers & partners
Unlock federated data potential
Across boundaries
Build, deploy, and operationalize ML-based products on a federated infrastructure spanning organizational and geographical boundaries.
Reduce costs and risk
Reduce risks and eliminate costs associated with centralizing data.
Enhance your data partnerships
Enhance your partnerships with access to third-party data or building a federated data ecosystem.
Build new ML products
Use a federated infrastructure to build new ML-enabled products or run existing models against additional federated data sets.
Explore the Apheris platform
Apheris Compute Gateway
Data custodians can make data accessible for advanced analytics and machine learning without sharing data.
Apheris Compute Orchestrator
Allows for ML and analytics to be run across multiple federated datasets while ensuring raw data is never returned from the data sources.
Apheris SDK
Use a variety of machine learning tools, frameworks, and libraries to bring your existing data pipelines and models and run them in the Apheris platform.
Private
Rely on our strict asset policies, privacy controls, and data protection measures to ensure private data stays private and regulatory requirements are always fulfilled.
Secure
Strict isolation between tenants, encryption of data, and frequent third-party penetration tests are just a few of the security safeguards implemented to prevent unauthorized access, data breach, or IP leak.
ISO 27001 certified.
Governed
Logging of data access, helps you fulfil audit and compliance responsibilities. Robust asset policies reliably control who can access data and for what purpose.
Securely working across organizational boundaries
Manufacturing
"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
Resources
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.
White Paper
Beyond MLOps - How Secure Data Collaboration Unlocks the Next Frontier of AI Innovation
DevOps and MLOps are common methodologies in every company that wants to become software and data science driven by weaving AI into the core fabric of their business. Read what is required to securely collaborate with partners on data and AI at scale.
Guide
Buyer's Guide to Secure Data Collaboration
Secure data collaborations with multiple parties are the next source of getting a competitive edge. However, only a few data leaders know what to look for to get projects going. This buyer's guide will help you evaluate platforms and highlight considerations for AI and analytics across organizational boundaries.