Demand for AI infrastructure is unlike anything we have seen in over two decades of open networking and optical distribution. NeoClouds and sovereign operators are standing up AI factories at an unthinkable pace, and in the rush to secure GPUs, power, and floor space, one truth keeps getting learned late: an AI factory is not a list of parts you buy. It is a system that has to work together on day one.

A GPU cluster is only as productive as the fabric that feeds it, the optics that carry the traffic, the cooling that keeps it from throttling, and the software that shows what is happening inside it. Get one layer wrong and the most expensive assets in the building sit idle. The operators who win treat the buildout as a validated stack, not a procurement exercise. At EPS Global, we have spent the last year assembling exactly that: best-of-breed technology at every layer, pre-validated and delivered through a single relationship.

Silicon and switching

Everything starts with merchant silicon. Broadcom's Tomahawk 5 delivers 51.2 Tbps of switching capacity, with Tomahawk 6 pushing higher. Because the same proven chip appears across multiple vendors, operators are never locked into one roadmap.

On that silicon we bring three switching partners:

• Edgecore's open, ONIE-enabled platforms, including the Tomahawk 5-based AIS800 series and AGS8200 AI server, offer air, liquid, and immersion cooling built in.
• Celestica, a Dell'Oro-recognized leader in AI-networks Ethernet switching, brings the DS5000 at 64 x 800G and the DS6000 family reaching 1.6 TbE.
• UfiSpace extends the same open approach to the edge, where segment routing matters for distributed inference.

The network operating system

Hardware without the right software is just a box. SONiC, the open-source NOS Microsoft built for Azure, now runs on millions of switches, and EPS Global is one of only two companies providing Broadcom Enterprise SONiC support, giving operators openness with production-grade backing. For a commercially owned NOS, IP Infusion's OcNOS Data Center delivers a lossless 800G fabric with the RoCEv2, PFC, and dynamic load balancing AI traffic demands. Aviz Networks adds multi-vendor observability on SONiC, and Hedgehog brings a cloud-native VPC experience to private AI clouds, so operators get a hyperscaler feel without a specialist fabric team.

Intelligence and interconnect

Two layers are easy to overlook and expensive to ignore.

Visibility at the fabric level

Modern fabrics suffer gray failures and congestion that second-by-second monitoring cannot see. Aria Networks pulls telemetry off the chip at microsecond resolution and uses AI to detect and resolve issues across the whole fabric, spanning the NIC, transceivers, and switch.

The connection between sites

This becomes first-class as power pushes operators into more locations and inference moves closer to users. Here MaiaEdge applies Federated Private Networking. Its Path Border Controller edge device pairs with the cloud-native Path Computation Engine to activate deterministic private paths automatically, with no CLI, BGP, or MPLS complexity and full hop-by-hop visibility. It sits alongside existing infrastructure rather than requiring rip-and-replace, and lets operators offer cloud on-ramps to AWS, Azure, and Google Cloud under their own brand, keeping the customer relationship, margin, and sovereignty while onboarding tenants in minutes.

Optics, connectivity, power, and cooling

None of this moves a bit without the physical layer, where many projects quietly stall. Optics are the clearest case of demand outrunning supply: EPS Global has partnered with Coherent for over 25 years and is one of their largest global distributors, and their transceivers and active optical cables carry the traffic AI fabrics depend on. Amphenol and Proficium complete high-density connectivity, with Proficium adding connected-infrastructure design purpose-built for AI sites. And with a single AI server drawing around 6 kW, Vertiv's power and thermal-management infrastructure, alongside built-in liquid and immersion cooling, keeps dense racks running rather than throttling.

Why one relationship beats thirteen

Each layer is a specialist market with its own vendors, lead times, and validation quirks. Sourcing them separately means discovering integration gaps in production, the worst place to find them. Assembling them as a validated stack removes that risk: operators select the best technology at each layer and receive it as one integrated solution, backed by EPS Global's logistics, pre-configuration, and pre-sales engineering across 28 locations, tested in our switch lab.

This matters most for operators building inference, who are not hyperscalers with armies of engineers. Every engineer they do not have to hire is capital they can put toward more GPUs, and more network.

Building or scaling an AI cluster? Talk to the EPS Global team about a validated stack tailored to your workload, your sites, and your timeline.