Local data, cloud services.Keep the data. Use the tools.
With local data, cloud services, sensitive data stays on single-tenant hardware in a location you can name. Only the records or results a cloud analytics or AI service actually needs leave your rack.
Local data with cloud services on top.Not everything has to move to use the cloud.
Public clouds offer analytics and AI services that are hard to build yourself. Using them often seems to mean moving all your data into the cloud first. For regulated or sensitive data, that is a big step.
This pattern keeps the system of record on your own cluster, on single-tenant hardware with private VLANs. A defined subset, such as de-identified records, aggregates or features, goes to the cloud service over a private connection. Results come back to the cluster.
How the pattern is laid out.Each piece has one job.
- System of record
- Single-tenant cluster: no other customer on your nodes, disks or switches.
- Location
- Chicago, Ashburn, Los Angeles, or your colocation facility.
- What leaves
- Only the data a cloud analytics or AI service needs, defined with your team.
- Transfer path
- Private connections to AWS, Azure or Google Cloud where available.
- Access
- Management over a separate out-of-band network, staffed by U.S.-based engineers.
Where it fits.Teams that need both.
Healthcare
Patient data stays in a known rack on private networks, designed to support HIPAA requirements.
Learn moreFintech
Transaction data stays on a private fabric while selected data feeds cloud analytics.
Learn moreAI and analytics
Run GPU and high-compute nodes next to the data, and use cloud services where they help.
Learn moreWhy the boundary matters.Smaller copies, clearer audits.
Every copy of sensitive data is something to secure, track and explain in an audit. When only a defined subset leaves your cluster, there is less to track and a clearer answer to where the data lives.
The full data set stays on hardware no other customer shares, behind private VLANs, in a physical location you can name. Immutable backups protect it from changes or deletion once written.
Questions, answered.
Does this make us compliant?
It is designed to support requirements like HIPAA and PCI by keeping sensitive data on single-tenant hardware in a known location. We do not claim certifications.
Who decides what data goes to the cloud?
Your team does. We help define the subset during design and build the transfer path around it.
Could we run the AI models on the cluster instead?
Often, yes. GPU and high-compute nodes can run inference next to the data. Many teams mix both.
Which cloud services can we use?
Analytics and AI services in AWS, Azure or Google Cloud, reached over a private connection where one is available for your provider and metro.
Keep exploring.
Talk to the engineers who will build it.
Tell us what you run today and where you’re headed. We’ll come back with a design and a fixed monthly price.