The AI Factory, Delivered as One System
Radiant finances, builds, and operates data centres, AI hardware, and managed services as a single platform — under one contract, through one control plane.
Most AI infrastructure is assembled from separate providers for capital, land, hardware, software, and operations. Radiant owns all five and operates them as one platform. The result is a single system with one contract, one control plane, and one team accountable for it end to end.
Run workloads,
not infrastructure
Bare Metal
Dedicated clusters from thousands to tens of thousands of GPUs, with a full lifecycle control surface.
Virtual Machines
Governed, tenant-isolated GPU instances with drivers, frameworks, policy, and identity applied at provisioning
Managed Kubernetes
GPU-native Kubernetes, operated across control planes, node pools, and the accelerator stack.
Managed Slurm
The scheduler ML teams use, on Kubernetes-operated infrastructure.
Managed Storage
Parallel file, object, and persistent storage tuned with compute.
Managed Networking
InfiniBand, Spectrum-X RoCE, and Ethernet, deployed per workload, with tenant-isolated domains.
Compute, network, and storage, co-engineered
Compute
Blackwell-class GPU systems and Vera Rubin-ready architectures, deployed in NVIDIA AI factory patterns and tuned per customer across GPU generation, topology, interconnect, and tenancy.
Network
Quantum InfiniBand and Spectrum-X fabrics on purpose-built pathways: short-reach DAC geometry, overhead containment for long fiber trunks, and physical segregation of power and data paths.
Storage
High-throughput storage fabrics and NVMe-over-Fabrics paths co-engineered with the compute rows.
Powered land, built shells, carrier-neutral connectivity
The platform stands on a large powered-land portfolio and deployable capital at the scale AI factories require. Facilities are engineered for density from the ground up: high-density electrical design, liquid-to-air cooling readiness with pre-plumbed CDU loops, behind-the-meter power, and digital-twin airflow modeling.
One control surface across the platform
Every layer reports into FlightDeck. Operators see the whole platform; teams see their slice of it.
FlightDeck correlates capacity, utilization, health, storage throughput, network congestion, quota pressure, and workload impact across every tier. It also drives node lifecycle, fault isolation, self-healing recovery, capacity planning, and policy enforcement across tenants, regions, and operating domains.
Behind it is Radiant's operations team: cluster bring-up, burn-in, topology validation, and storage and network tuning, run by engineers who operate AI factories.
