Inferx

The full-stack engine for
industrial-scale AI

Turn raw silicon into sovereign AI factories with Radian Arc's InferX NCP enablement platform

Stop building fragile, fragmented infrastructure with unvalidated hardware and mismatched software. The InferX validated GPU architecture solution delivers a performance-engineered, full-stack alternative to hyperscale AI clouds based on a focused, expert-led approach to AI outcomes with maximized intelligence per Watt.

By unifying a flexible hardware foundation, intelligent orchestration, and a centralized control plane, InferX shifts your operational model from managing complex and siloed infrastructure components, to delivering predictable AI outcomes.

Fully aligned with NVIDIA Cloud Partner specs
Complete full-stack accountability - from silicon to tokens
Maximized "intelligence per Watt" across heterogeneous infrastructure
The core philosophy

The power of a unified, validated stack

Most enterprise AI projects stall out because they attempt to mix unsupported switch, storage, and driver combinations on arbitrary hardware. InferX eliminates this architectural risk by providing an operated, validated cloud service where compatibility, compliance, and performance engineering are handled for you.

Through a strictly validated, dual-plane architecture stretching from localized edge nodes to massive core data centers, InferX ensures every ounce of power yields high-value computational output.

The full-stack breakdown

The InferX full-stack approach

InferX replaces chaotic, multi-vendor guesswork with a vertically integrated, four-tier framework that defines clear boundaries of consumption and operational responsibility.

Applications

We work with a network of ISV developers to deliver AI-powered solutions tailored to business needs, from conversational AI and computer vision to predictive analytics, automation and industry-specific use cases. Applications are built on a flexible foundation that enables rapid innovation, scalable deployment and maximum intelligence per Watt.

AI control plane

A unified orchestration layer that intelligently selects the optimal model, infrastructure and deployment location based on performance, cost, compliance and latency. It provides governance, monitoring and lifecycle management across the entire AI estate.

GPU infrastructure

High-performance AI compute spanning core data centers, regional hubs and edge locations. Optimized GPU clusters provide the scalability, resilience and performance needed to train, fine-tune and run demanding AI workloads.

Federated networks

Radian Arc enables a secure, interconnected network that links disparate compute clusters across data centers and telco operators, allowing for intelligent workload routing based on availability and capability.

The right workload.
The right model.
The right location.

The Deployment Journey / Roadmap

The path to production-scale ernablement

InferX removes architecture and operational risk by following a highly disciplined, 4-step development and validation methodology:

01
Development foundation

A minimum environment of 30+ nodes dedicated strictly to platform development, lifecycle workflow testing, and functional software validation.

02
Customer-scale validation

Scaling up to a 1 MW+ footprint across hundreds of GPUs, where real-world operational benchmarking and proof-of-scale data become meaningful.

03
NCP evidence path

Rigorous logging of benchmarking, observability, security controls, and incident/change processes to fulfill formal NVIDIA Cloud Partner validation milestones.

04
AlaaS + federation

Full production rollout of managed inference endpoints, advanced RAG/data services, intelligent placement policies, and automated cross-site reconciliation.

Eliminate fragmentation. Own the full stack.

Don’t get caught trying to piece together a fragmented AI infrastructure stack that burns energy in idle cycles. Standardize on a unified, performance-engineered system designed to deliver maximum intelligence per Watt, absolute hardware flexibility, and secure, localized AI outcomes.