AI and Compute Infrastructure

Purpose-built facilities for next-generation AI workloads — engineered for the power densities, cooling demands, and network performance that accelerated compute requires.

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The Challenge

AI requires infrastructure that does not exist off the shelf

General-purpose data centers are built for enterprise IT: servers drawing 5–15 kW per rack, standard air cooling, and conventional 1/10 GbE networking. AI compute clusters bear no resemblance to this workload profile.

IOXN designs and develops facilities specifically for AI and HPC — where every engineering decision, from the electrical switchgear to the fiber routing, is made with accelerated compute in mind.

Sustained power loads of 30–100 kW per rack require specialized electrical infrastructure most commercial facilities are not built for.

GPU thermal management at scale demands precision cooling that air-only systems cannot reliably deliver.

Distributed training requires ultra-low latency fabric interconnects between hundreds or thousands of accelerators.

AI operations require 100% uptime — any power or cooling failure during a training run destroys the entire job.

GPU clusters require structured cabling for thousands of high-bandwidth optical connections within the facility.

Technical Specifications

Facility specifications

Power per Rack

Up to 100 kW

Standard configurations from 10–40 kW, dense AI clusters to 100 kW+

Cooling Technology

Air / Liquid / Immersion

Rear-door heat exchangers, direct liquid cooling, and full immersion options

Network Fabric

200 Gbps – 800 Gbps

InfiniBand NDR and Ethernet RoCE v2 for GPU-to-GPU interconnects

Power Redundancy

2N UPS and Generator

Dual-corded feeds with independent UPS modules and diesel or gas generation

PUE Target

< 1.25

Optimized mechanical and electrical design for compute-intensive loads

Physical Security

Tier-III / IV

Biometric access, 24/7 CCTV, mantrap entry, seismically assessed

Facility Design

Engineered from the ground up for accelerated compute

Our AI facilities begin with a power and cooling study — defining the electrical infrastructure, cooling topology, and network architecture before a single structural element is designed. This ensures every system is optimized for sustained high-density operation.

Structural, mechanical, electrical, and network engineering are coordinated as a single integrated design — not sequenced trades working from separate briefs.

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Use Cases

Who we build for

Large Language Model Training

Multi-thousand GPU clusters demand power densities and interconnect bandwidth that standard enterprise facilities cannot support. IOXN facilities are designed from the ground up for this workload class.

AI Model Inference at Scale

Low-latency inference serving requires proximity to users and reliable network paths. Our edge and colocation facilities provide the predictable performance inference applications demand.

Autonomous Systems Testing

Simulation and sensor data processing for autonomous vehicles and robotics places unique demands on real-time data ingestion, compute density, and storage throughput.

Scientific and Research HPC

High-performance computing for genomics, climate modeling, and materials science requires managed, scalable compute environments with high storage I/O and flexible networking.

Infrastructure Pillars

Three systems that must work together

Power at Density

Delivering 30–100+ kW per rack requires a complete rethinking of electrical distribution: dedicated transformers, higher-voltage distribution (415V and 480V), precision PDUs, and independent UPS modules per cluster.

Thermal Management

GPU thermal dissipation at 300–700W per chip demands active cooling solutions beyond standard CRACs. Rear-door heat exchangers, direct liquid cooling manifolds, and full-immersion tanks are deployed based on rack density and workload profile.

Fabric Networking

Training large models requires tight coupling between thousands of GPUs. IOXN facilities are pre-structured for InfiniBand NDR (400 Gbps) and RoCE v2 fabrics, with pre-planned optical pathways and low-loss structured cabling.

Building an AI compute cluster?

Tell us about your compute requirements. We will help you understand what infrastructure is needed and how to get there.

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