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Accelerate your AI Factory

The Aviz ONE Center for AI Factory helps enterprises, GPU cloud providers, and neo-cloud operators continuously validate end-to-end AI infrastructure designs—accelerating deployment and ongoing optimization as the ecosystem evolves.

Stay one step ahead with the best-in-class AI factory designs.

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The Challenge

AI infrastructure risk is increasingly integration-driven. Multi-vendor stacks evolve faster than validation cycles, while organizations demand open architectures with predictable outcomes.

Where It Breaks

AI factories don't fail because one component is "bad." They fail when the full stack doesn't operate as one system at scale.

An AI factory is a full stack

GPU compute
DPU / NIC
Switching
Network OS
Storage
Orchestration

Business Impact

AI initiatives stall not because of models—but because infrastructure can't operate reliably at scale.

  • Many AI POCs never reach production
  • Integration and operational readiness are the primary blockers
  • Delays and rework increase cost and reduce confidence

The Cost of Finding Issues Late

Most failures show up after time and money are already committed.

01
During proof-of-concept
Integration gaps surface when components first meet real workloads.
02
During early production
Reliability, scaling, and operations expose hidden dependencies.
03
After infrastructure spend is locked in
Fixes become rework—slowing rollout and increasing cost.

Impact for GPU Cloud Providers & Neo-Clouds

Time to market
Customer onboarding
Service reliability
Capital efficiency

Why Aviz AI Factory

Aviz ONE Center for AI Factory shifts validation left — before deployment. Instead of discovering issues after rollout, organizations can validate full-stack designs upfront in a neutral environment.

Outputs include

Production-ready Reference Architectures
Deployment configuration packages
Validation evidence
Operational guidance

Sales, platform, and engineering teams can use these artifacts directly.

What Aviz AI Factory Framework Validates
Full-Stack Design Assurance — Not Performance Benchmarking
Focus: correctness, interoperability, and operational readiness.
Scope of Validation
AreaDescription
GPU Backend Fabric (East-West)Scale-out networking for distributed AI training clusters
Front-End and Storage Fabrics (North-South)User access, ingestion pipelines, and storage connectivity
Compute IntegrationGPU servers, NICs, and DPUs operate as a unified platform
Orchestration LayerKubernetes and platform management integration
Storage AttachmentData paths required for AI workloads
Monitoring and OperationsObservability and lifecycle workflows
Supported Stack
Aviz validates combinations across the AI infrastructure ecosystem and keeps them current through continuous regression testing.
Supported Stack
TierFunctionVendors / Platforms
Tenant / Workload OrchestrationKubernetes & VM Platforms
Rafay · Spectro Cloud · Red Hat OpenShift · Mirantis
Infrastructure OrchestrationService, Compute, Host Networking
Aviz Open Networking Enterprise Suite (ONES)
ComputeGPU Platforms
NVIDIA DGX · HGX · NVL
NetworkingFabric (East-West, North-South)
SONiC · NVIDIA Cumulus Linux · Hybrid Ethernet / InfiniBand · Multi-vendor Switching
NICs / DPUsAccelerator Networking & Offload
NVIDIA ConnectX · NVIDIA BlueField · Accelerator networking platforms
StorageAI Storage
VAST Data
Operations & VisibilityMonitoring, Telemetry, Lifecycle Operations
Aviz ONES Dashboards · Fabric Observability
Capability Coverage, Multi-Tenant AI Infrastructure
The Aviz ONES AI Factory Center validates constructs required to productize shared AI infrastructure.
Tenant Isolation
  • DPU-based isolation
  • VXLAN / EVPN network isolation
  • VLAN and VRF segmentation
Virtual Network Services
  • Overlapping IP support
  • Subnets and gateways
  • DHCP services
Connectivity
  • Internet and NAT gateways
  • Peering and routing
Service Exposure
  • Load-balancing constructs for Kubernetes and mixed workloads
Observability
  • Network telemetry
  • Congestion monitoring
  • Health validation
Operations Readiness
  • Maintenance workflows
  • Upgrades
  • Audit logging
  • Role-based access control

Validation Workflow

Design → Validate → Publish

Each validated design becomes deployment-ready guidance.

1
Select Stack
Define compute, networking, storage, and orchestration components.
2
Day‑0 Bring-Up
Infrastructure connectivity and baseline configuration.
3
Day‑1 Tenants
Isolation, storage integration, and workload readiness.
4
Day‑2 Operations
Monitoring, upgrades, and lifecycle management.
5
Publish Artifacts
Reference Architecture and validation reports.

Always-On Validation

AI infrastructure evolves continuously. Validation must as well.

01

Reporting Outputs

Validation dashboards, failure digests, compatibility updates, and ecosystem reports.

02

Workload Smoke Test

Lightweight container-based training, minimal inference sanity, storage read/write path included. Telemetry captured across ports/queues + RoCE signals + GPU/host health.

Partner Ecosystem
Validated partners by category. Want your stack validated and published as a co-branded Reference Architecture? Become a partner.
Compute
NVIDIA DGX · HGX · NVL
NICs / DPUs
NVIDIA ConnectX · NVIDIA BlueField · Accelerator networking platforms
Networking
SONiC · NVIDIA Cumulus Linux · Hybrid Ethernet / InfiniBand · Multi-vendor Switching
Storage
VAST Data
Orchestration
Rafay · Spectro Cloud · Red Hat OpenShift · Mirantis
Operations
Aviz ONES Dashboards · Fabric Observability

Pre-Validated AI Infrastructure, Before You Buy

For enterprises, GPU cloud providers, and neo-cloud operators building the next generation of AI infrastructure. Design with confidence. Deploy without surprises. Operate at scale.