Federated infrastructure
No need to centralize data
Work across organizational and geographical boundaries
Unlock inaccessible data for machine learning
Watch: Data Custodian Demo
Apheris Compute Gateway - no need to move data
Leverage federated data sources
Deploy anywhere
Flexibility on compute
Data custodians stay in full control, always
For any computation request from a user, asset policies are validated at multiple points throughout the platform. Additionally, data custodians can approve incoming compute requests and control what results leave their Compute Gateway. This ensures that results are returned to the data scientist without exposing data or IP.
Technical specification
- Deployment using infrastructure-as-code (Helm Charts, Terraform) provided by Apheris into a Kubernetes cluster.
- Apheris provides reference deployments for all major cloud providers (AWS, GCP, Azure) and on-premises deployments.
- As an alternative to deploying the Compute Gateway into an existing Kubernetes cluster, Apheris also provides a standalone installer, which includes a lightweight Kubernetes distribution.
Supports large computational workloads. For example, large foundational ML models.
Stay compliant
Data doesn't need to move
Integrate into your tech stack
Private & secure
Multiple privacy-enhancing technologies allow users to set the appropriate level of privacy for the type of data so that maximum value is extracted from any dataset.
Each action on the Apheris Platform is logged for full auditability and enforcement of the asset policies.
Governed
Trusted by our customers & partners
Address today's challenges. Make data accessible.
Reduce risks and costs
Enhance partnerships
Monetize your data
Working with data partners is easier with Apheris
"When I think about Apheris, I think about acceleration. We were able to accelerate the onboarding of new partners by months, which also leads to much faster development and evolution of our own data products."
Resources
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.
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.
Infographic: What are Collaborative Data Ecosystems?
The world's biggest challenges are going to be solved in Collaborative Data Ecosystems. Learn how in our free-to-access infographic!