Leader in ISG Private Cloud Report 2026.

UnitedLayerBlue Version

UnitedLayer + NVIDIA

GPU power
for AI and
HPC, in
your private
cloud.

UnitedLayer partners with NVIDIA to deliver GPU-accelerated infrastructure for AI, deep learning, high-performance computing and cloud. Train, fine-tune and serve models on a secure, fully managed private cloud, and run inference at the edge where your data is created.
Find where to run AI
Try the console

Best

Private Cloud for AI Workloads, Global Titans 2025
0 %
Platform availability

3U

UnitedEdge® AI appliance for the edge

24/7

Managed and supported
gpu.unitedlayer / example-research
GPU pool · 16 GPUs
AI
DATA

GPU jobs

Example tenant · illustrative figures
GPUs in use0
Jobs running0
Queued0
Edge sites live0
Job · type · GPUsStatus
Built For Ticker
Built for

Solutions offered

GPU-accelerated, from the
data center to the edge

Faster processing, scalable infrastructure and AI integration for your most demanding workloads.
GPU Solutions Tabs

GPU-accelerated solutions

Faster processing, scalable infrastructure and AI integration for your most demanding workloads.

  • Faster processing
  • Scalable infrastructure
  • AI integration
GPUGPUGPUGPU
GPU-accelerated solutions

United Private Cloud® for AI workloads

One platform for the
whole AI lifecycle

An end-to-end, scalable and secure private cloud for AI development, training and inference.
Pick a stage to see what runs there.

See it in motion

Watch GPUs at work

Seven moments on UPC NVIDIA Cloud Infra, from a training run to inference at the edge.
Train and serve in-house. A model trains on NVIDIA GPUs, then goes live for inference while data stays in your cloud. Illustrative.Keep every GPU busy. Research and simulation jobs are scheduled across a GPU cluster and results come back sooner. Example jobs.Train in the core, answer at the edge. A new model trains centrally, deploys to clinic, plant and store, and feedback flows back.Elastic GPUs at the edge. GPUs, vCPUs and RAM follow inference demand up and down while response time stays steady.Answers from next door. The same request served by a nearby edge site and by a distant cloud region. Illustrative.VMs, containers and serverless. Steady apps on VMs, microservices in containers and events on serverless, on one platform.Sovereign AI, end to end. Data, training, model and inference stay on dedicated GPUs inside your boundary.
LIVE · AUTO-PLAYING

Where should it run?

Core, edge, or both?

Tell us about the workload and see where it fits best: GPU clusters in United Private Cloud®, a UnitedEdge® AI appliance on site, or a hybrid of the two.
What kind of work is it?
How fast must answers come back?
Where is the data created?
How big is it?
How we would run it

    A starting point only. Our AI infrastructure architects size GPUs, storage and networking with you.

    Designed for enterprise innovation

    An AI-first private cloud

    GPU-accelerated infrastructure

    NVIDIA GPUs for AI, deep learning, HPC and cloud.

    Multi-factor private cloud

    VMs for control, containers for microservices, serverless for low overhead.

    Any containerized workload

    Public and private image repositories supported.

    Re-architect for AI

    Virtual infrastructure scales up or down with demand.

    Edge AI

    UnitedEdge® AI: a 3U appliance built as two mirrored halves.

    Control data, latency and compliance

    Processing close to the source, for IoT and 5G.

    Immutable backups

    Threats detected and neutralized before they hit operations.

    Built-in intelligence layer

    Observability, cloud management and agentic orchestration.

    Fully managed

    Secure infrastructure, run for you 24/7.

    Global Titans 2025

    Best Private Cloud for AI Workloads

    Recognition for United Private Cloud® for AI.

    ISG

    Leader, 2026

    Fourth consecutive year as a leader in private/hybrid cloud and data center services.

    Banking · Oracle

    15-min RPO · 1-hour RTO

    Production in San Francisco, recovery in Las Vegas, drilled twice a year.

    Energy utility

    Hybrid, multi-cloud and edge

    Assets discovered, costed and measured for carbon across every environment.

    How it works

    From first model to
    production AI in five steps

    Side by side

    Three ways to get GPUs

    AreaBuy GPU serversPublic cloud GPUsUPC NVIDIA Cloud Infra
    Getting startedProcurement, power, coolingFast, if capacity is freeManaged GPU infrastructure, ready for you
    Your dataStays with youMoves to a shared cloudStays in your private cloud or at the edge
    ScalingBuy moreOn demand, at a priceScales up or down with demand
    Edge inferenceYour own appliancesRound trip to a regionUnitedEdge® AI on site
    Workload shapesWhatever you buildSeparate servicesVMs, containers and serverless on one platform
    OperationsYour teamYour team, provider toolsFully managed, 24/7
    Questions

    What teams ask before they start

    What can we run on UPC NVIDIA Cloud Infra?

    closed Icon Opend Icon

    AI development, training and inference, deep learning, high-performance computing and research, and general cloud workloads that benefit from GPU acceleration.

    Can AI run at our sites instead of a data center?

    closed Icon Opend Icon

    Yes. UnitedEdge® AI brings inference to clinics, plants, trading floors and stores in a 3U appliance built as two mirrored halves, so one component failure does not stop inference.

    How does the hybrid model work?

    closed Icon Opend Icon

    Training runs on GPU clusters in United Private Cloud®, and models deploy to edge sites for low-latency answers, balancing performance and scale.

    Do we have to use containers?

    closed Icon Opend Icon

    No. The platform runs VMs, containers and serverless, and any containerized workload with public or private image repositories.

    Which GPUs are available?

    closed Icon Opend Icon

    GPU configurations are designed with you for each workload. Talk to our architects about current options.

    ↑