Put your private GPU infrastructure into production with confidence.
A design your teams can support
Define the GPU platform, network choices, software versions and integration responsibilities before deployment.
Evidence before acceptance
Agree the tests and operating handoffs that establish readiness for production.
Visibility across team boundaries
Bring network and infrastructure evidence into the same investigation, with a clear owner for the next action.
GPU infrastructure first
Turn the purchase into an operating plan.
A private GPU cluster brings compute, storage, networking and platform teams into the same project. Aviz helps define the network design and the evidence each team needs to accept and operate it.
- Agree the supported design
Map GPU connectivity, storage, front-end and management networks. Record the hardware, software versions, controllers and interfaces.
- Rehearse and validate
Use DSX Air where appropriate for logical rehearsal, then test the assembled stack and agree the outstanding issues.
- Establish ownership
Define provisioning, monitoring, change, recovery and vendor-escalation responsibilities across compute and networking.
- Prepare the operating team
Deliver the runbooks, acceptance evidence and training needed for day-to-day operations and the next expansion.
Aviz capabilities
A practical operating layer for your GPU investment.
Begin with network readiness and lifecycle operations. Add service connectivity and inference visibility where your private AI service requires them.
Aviz ONES
Commission and operate the factory network.
Use reference-design-based bring-up, tenant network automation and lifecycle visibility on the supported configuration. Connect to the controllers and orchestration tools your teams operate.
Explore ONESAviz Service Gateway
Connect private capacity to the rest of the enterprise.
Add tenant-aware routing and service-edge policy for shared services, other data centers and cloud connectivity, according to your network design.
Explore Service GatewayAviz AI-Parser
Measure the private inference service.
Where supported traffic is available, associate inference usage and response timing with the tenant or service. Use that evidence alongside GPU and network telemetry.
Explore AI-ParserAviz AI NOC
Give operators a shared investigation view.
Evaluate evidence-based correlation across supported GPU, compute, inference and fabric sources. Early-access engagements retain operator control.
Explore AI NOCQualified network choice
Choose the fabric that fits the GPU design and the team running it.
Aviz starts with the reference architecture and the role of each network. That may include NVIDIA Spectrum-X Ethernet, InfiniBand and controller-managed NVLink, with supported Ethernet choices for other parts of the estate.
Evaluate SONiC where it fits the hardware, features and support model. Agree a validated combination and a migration or deployment plan your network team can maintain.
Experience that transfers
Bring AI factory operating experience into your enterprise team.
Aviz applies engineering experience from NeoCloud and NVIDIA-based AI factory environments to enterprise infrastructure. Forward-deployed engineers bring networking expertise and AI factory training to design reviews, integration work and operational handoff.
Your compute, network and platform owners work through the same acceptance criteria. The result is a documented support boundary and a practical plan for keeping the environment current.
Beyond the GPU cluster
Modernize the networks you already operate.
The AI factory can be the starting point for a broader network plan. Address each part of the estate with the capabilities and support it needs.
SONiC modernization
Qualify supported switching hardware and SONiC software, validate the design and equip your operators with ONES, training and support.
Explore the capabilityNetwork observability
Use Aviz Packet Broker and Service Nodes to feed relevant traffic and metadata into your existing investigation and analytics workflows.
Explore the capabilityAI-assisted network operations
Use Network Copilot for supported network investigations and evaluate AI NOC for broader AI factory correlation.
Explore the capabilityQuestions from enterprise infrastructure teams
- Start with the GPU platform, planned deployment size and the reference architecture. Aviz will work with your compute and network teams to map the different network roles, select a supported combination and define commissioning tests. This gives procurement and implementation a common technical basis.
Trusted across the AI infrastructure ecosystem
























