AI and analytics infrastructure.Compute beside your data, with no transfer bills.
Our AI and analytics infrastructure puts GPU and high-compute nodes on the same private fabric as the data they process. You pay one monthly price for the rack, with no egress fees as your datasets grow.
AI and analytics work best near the data.Moving data costs time and money.
Analytics jobs and AI models read a lot of data. When compute and storage sit in different places, every run moves that data across a network, and in many clouds every gigabyte out adds to the bill.
Infraclusters puts GPU and high-compute nodes on the same private switching fabric as your storage. Data stays in the rack, and your price stays one monthly figure.
Why the rack changes the math.Same work, different bill.
What AI and analytics teams run.From reports to models.
Real-time analytics
Reporting and analytics on high-memory nodes with NVMe storage pooled by Ceph.
Learn moreAI inference
Trained models close to users and data, with GPU nodes where needed.
Learn moreVideo and sensor analytics
Process camera and sensor streams near the source and send results upstream.
Learn moreGrow as your data grows.One node at a time.
Add nodes as datasets and models grow, from a custom footprint to a full rack. Each node brings processors, memory and disks together. A full rack can combine compute, storage, GPU and network nodes on your own switching.
Ceph keeps three copies of every block on different nodes, so a failed disk does not stop a long analytics job or take a model offline. Our U.S.-based engineers replace the hardware and the storage rebuilds on its own.
Questions, answered.
Which GPUs do you use?
We choose GPU nodes during the design session based on the models you run and how you serve them. Every build is quoted at a fixed monthly price.
Do you charge to move data in or out?
No. There are no egress fees, no per-request storage charges and no surprise tiers. You pay one monthly price for the rack.
Can I keep training in a public cloud and run inference with you?
Yes. We offer private connections to AWS Direct Connect, Azure ExpressRoute and Google Cloud Interconnect, with options confirmed per provider and metro during design.
Can I start small and add GPU capacity later?
Yes. Start with a custom footprint and add GPU or high-compute nodes as models and datasets grow, up to a full rack.
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.