SHTS LLC sources AI compute through TD SYNNEX and Ingram Micro distribution — NVIDIA RTX PRO Blackwell GPUs, GPU servers, fast local and shared storage, high-speed networking, and the rack power and cooling that has to exist before any of it turns on.
The GPU is the easy part. What sinks AI projects is everything around it: a 600W card in a chassis rated for 400, a workstation that starves a GPU on PCIe lanes, a rack that trips a breaker the first time four cards spin up together. That is the conversation you get here first.
The whole Blackwell workstation line, with the two numbers that actually decide your build: how much ECC memory you get, and how many watts it costs you. All PCIe 5.0 x16 with GDDR7 ECC memory.
RTX PRO 6000 · 96GB
Three variants, same 96GB and same 24,064 CUDA cores. Workstation Edition at 600W in an extended-height card, Max-Q at 300W in a standard dual slot, and a Server Edition for chassis deployment.
RTX PRO 5500 / 5000
Where most serious local-inference work actually lands. The 5000 runs the same 300W envelope as a Max-Q 6000 with 48GB or 72GB, and still supports MIG partitioning into two instances.
RTX PRO 4500 / 4000
The practical answer for multi-GPU boxes and workstations with ordinary power supplies. The 4000 is a single-slot 140W card — four of them fit where two big cards will not.
RTX PRO 4000 SFF / 2000
For small-chassis and edge deployments with no auxiliary power available. 24GB or 16GB of ECC memory on a 70W card that runs off the slot.
Sourced through TD SYNNEX and Ingram Micro, plus direct vendor relationships with HPE, Cisco and Schneider Electric. Configurations are quoted per build — send the workload and the constraints.
GPU Servers
HPE ProLiant, Dell PowerEdge, Lenovo ThinkSystem and Supermicro GPU-capable chassis. The questions that matter are slot width, PCIe lane topology, PSU headroom and airflow — not the badge on the bezel.
AI Workstations
A GPU starved of PCIe lanes, system memory or storage bandwidth is an expensive space heater. Full builds with the CPU platform, ECC memory, NVMe and network sized to the card, or a custom build to your spec.
Storage & Networking
Local NVMe, shared storage and the 10/25/100GbE fabric between them. Training and inference are bandwidth problems long before they are FLOPS problems.
Rack Power & Cooling
Four 600W GPUs is 2.4kW of card before the rest of the machine. SHTS is a Schneider Electric partner — UPS, rack PDUs, enclosures and cooling specced against the actual load, not a guess.
SHTS buys through TD SYNNEX and Ingram Micro, the same distribution the large integrators use, and carries direct relationships with HPE, Cisco and Schneider Electric. You get that pricing without being handed to a sales rep who has never opened a chassis.
What you actually get is the spec conversation. How much memory the model really needs, whether the 300W card is the smarter buy than the 600W one, whether that server has the lane topology to run four cards or will quietly drop them to x8, and whether the rack can power it. Over a hundred custom machines built, by a working broadcast engineer who still gets the support call when a build is wrong.
If the honest answer is that you need less hardware than you think, you will hear that before the purchase order rather than after.
Related: RTX PRO 6000 Blackwell Max-Q · custom workstations · Thunderbolt expansion & rackmount Mac · business IT · government & education
Tell us what you are running, what chassis or rack it has to live in, and what the power situation is. You get a real line-item quote with lead times.