Why AI Data Centers Are Different

A traditional data center designed five years ago can host an AI workload the same way a parking garage can host a Formula 1 race — technically yes, you should not. Three IT-layer problems separate AI infrastructure from the room you have today; we own those three.

East-West Fabric

Inference is north-south; training is east-west. NVLink, InfiniBand, RoCE, and 400G/800G Ethernet need a switching plan and a cabling plan that traditional DC architects do not ship out of the box. This is core IP-network work.

GPU Node OS

Linux on a GPU training node is not the same Linux that runs your web tier. NVIDIA driver and CUDA toolkit version matrix, kernel tuning, NUMA pinning, huge pages — each one unprovisioned costs you 10–30% throughput.

Data & Model Stack

Training data is hundreds of TB through the network; inference reads weights from local NVMe at GB/s. Vector databases, training corpora, and model registries are databases — treated as such, with HA and backup, not as loose files on a share.

Engagement Scope

What We Deliver

We own the IT layer of your AI facility — network, OS, data, and physical install. We do not design the electrical or HVAC; we integrate with the facility team or contractor your building already has.

Network Fabric Design

East-West & North-South

Two-tier or three-tier Clos. We spec InfiniBand, RoCE, or pure Ethernet based on your model size and training topology — not on the vendor we like best. Cabling plan with bend radius and length budget delivered as a buildable doc.

NDR/HDR InfiniBand, 400G/800G Ethernet
Per-rack switch placement and uplink budget
Out-of-band management network

Server & OS Bring-up

GPU Nodes, Ready to Train

Linux install (Ubuntu / RHEL / Rocky), NVIDIA driver and CUDA toolkit pinned to a tested matrix, kernel tuning, huge pages, NUMA topology validated. Done by Linux experts who actually run training workloads, not by an installer wizard.

NVIDIA drivers and CUDA matrix locked per node
Kernel tuning, NUMA pinning, huge pages
Per-node burn-in with NCCL all-reduce validation

AI Data Stack

Training Storage & Vector DB

Shared filesystem for training corpora (NFS, Lustre, or GPFS as fits), local NVMe tiering for hot data, and the vector / RDBMS layer for retrieval. Designed by database experts — HA and restore tested before you load production data.

NFS, Lustre, GPFS, MinIO object storage
pgvector, Milvus, Weaviate, Qdrant
Backup verification and DR runbooks

Rack & Burn-in

Physical Install

Our Remote Hand engineers rack the GPU nodes, dress and label cabling per your standard, then run the burn-in. You inherit a working stack, not a parts list and a stack of unboxed cardboard.

Rack survey and pre-staging
Per-node burn-in and validation
Photo-documented cable plan

Where AI Data Centers Live

Three patterns cover almost every engagement. The right pattern depends on your real estate, your timeline, and how much of the facility lifecycle you actually want to own.

Greenfield Build

Empty room, blank slate. Your facility team handles power and cooling; we design and deliver the network fabric, the GPU nodes, the AI data stack, and the install — the entire IT layer above the floor.

Brownfield Retrofit

Existing room, new workload. We audit current density and topology, plan the fabric upgrade, and migrate the IT layer onto the new design without taking production offline. Best when you cannot afford a green-field rebuild.

Colocation Tenant

You rent space; we make the IT layer work inside the cage. Fabric design, GPU node bring-up, data-stack install, and Remote Hand for the racking. The colo provider supplies power and cooling; we do everything above.

How We Engage

Audit

Workload profile, growth model, network topology, OS and database baseline — captured in a two-day on-site assessment by an IP-network and Linux expert.

Design

Fixed-fee architecture deliverable: fabric BOM, node OS and driver matrix, data-stack plan, rack elevations, cabling plan, and a phased build schedule.

Build

Remote Hand engineers execute on-site; Remote Experts in network, OS, and DB supervise remotely. Phased so production keeps running through the migration.

Operate

Hand off to your ops team or to GrossGate Data Center O&M. Either way the runbooks, configs, and as-built documentation are yours from day one.