Any data, any size, anywhere
Want to know more about how Apheris can power your data infrastucture for federated machine learning and analytics?
Build, deploy, and operationalize ML-based products on a federated infrastructure spanning organizational and geographical boundaries.
Reduce risks and eliminate costs associated with centralizing data.
Enhance your partnerships with access to third-party data or building a federated data ecosystem.
Use a federated infrastructure to build new ML-enabled products or run existing models against additional federated data sets.
Data custodians can make data accessible for advanced analytics and machine learning without sharing data.
Allows for ML and analytics to be run across multiple federated datasets while ensuring raw data is never returned from the data sources.
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.
Rely on our strict asset policies, privacy controls, and data protection measures to ensure private data stays private and regulatory requirements are always fulfilled.
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.
Logging of data access, helps you fulfil audit and compliance responsibilities. Robust asset policies reliably control who can access data and for what purpose.
"With Apheris, we found the perfect partner for exploring privacy preserving data analytics and optimization along the value chain with our customers."
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Want to know more about how Apheris can power your data infrastucture for federated machine learning and analytics?