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(01) Vorlixtech

Where Complex AI MeetsHigh-Performance Compute

Bridging the gap between AI algorithms and physical power

Animated field of compute nodes rolling as a wave

(02)Services

Scalable Cloud & Compute Solutions

On-demand and dedicated GPU instances for scalable training and inference jobs without high upfront capital expenditure.

(03)About us

Compute infrastructure, delivered as a working system

Animated GPU rack with live telemetry
To provisioned0h

Vorlixtech sits between the model and the metal. We source and rack the accelerators, tune the stack that runs on them, and stay on the hook for uptime — so your team spends its time on the workload instead of the hardware.

  1. 01Latest-generation NVIDIA-class accelerators, racked and ready
  2. 02Dedicated or on-demand capacity with no long procurement cycle
  3. 03Interconnect, storage, and cooling specified for the workload
  4. 04Monitoring, patching, and hardware replacement handled by us

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GPUs under management

0.0%

Fleet availability

0h

Typical provisioning time

0/7

Engineering on call

(04)GPU Leasing

Pick the accelerator, we handle everything under it

Single stations for a research team, or a full rack for a training run. Every configuration ships with NVMe scratch, private networking, and root access.

  • RTX 5090

    $1,180 / mo

    24-core CPU · 128 GB RAM · 4 TB NVMe

    Memory
    32 GB GDDR7
    Best for
    Fine-tuning, rendering, single-node research
  • RTX 4090

    $860 / mo

    16-core CPU · 96 GB RAM · 2 TB NVMe

    Memory
    24 GB GDDR6X
    Best for
    Inference endpoints, prototyping, CI for models
  • H100 SXMPopular

    $3,940 / mo

    Dual 32-core EPYC · 512 GB RAM · NVLink

    Memory
    80 GB HBM3
    Best for
    Multi-GPU training, large-batch inference
  • H200 SXM

    $5,620 / mo

    Dual 32-core EPYC · 1 TB RAM · NVLink

    Memory
    141 GB HBM3e
    Best for
    Frontier-scale training, long-context serving

Indicative monthly rates for dedicated stations on a 3-month term. Hourly on-demand and annual reserved pricing available on request.

(05)What we do

From a single station to a managed cluster

Three practices, one team. Most clients start with leased capacity and grow into hardware supply and managed operations.

01

GPU station leasing

Dedicated RTX 5090, RTX 4090, H100, and H200 stations with root access, private networking, and NVMe scratch storage.

02

Cluster build-out

Multi-node training clusters with NVLink or InfiniBand fabric, shared storage, and job scheduling configured for your stack.

03

Hardware supply

Workstations, servers, accelerators, and spares sourced, burned in, and shipped with warranty and replacement cover.

04

Hybrid cloud design

Burst to public cloud for peaks while your steady-state workload runs on owned or leased capacity at a fraction of the cost.

05

Security & compliance

Isolated tenancy, encrypted volumes, scoped credentials, and audit logging aligned to SOC 2 controls.

06

Managed operations

Monitoring, driver and firmware patching, capacity planning, and hardware replacement handled without your team paging.

(06)Why Vorlixtech

Engineers on the call, not account managers

No capital lock-up

Lease the capacity you need this quarter instead of financing a fleet you will outgrow.

Provisioned in 48 hours

Stations from our standing inventory are racked, imaged, and handed over within two business days.

Transparent pricing

One rate per configuration. No egress surprises, no per-hour rounding games, no support tiers.

Yours to control

Root access, your images, your orchestration. We keep the floor running and stay out of your stack.

(07) How it works

  1. 01

    Scoping call

    We size the workload — model, batch, memory ceiling, throughput target — and tell you what hardware it actually needs.

  2. 02

    Configuration

    You get a written spec and a fixed price: accelerators, host, storage, fabric, and the software image on top.

  3. 03

    Provisioning

    Stations are racked, burned in, and benchmarked before handover, with credentials and monitoring access included.

  4. 04

    Run & scale

    We watch the fleet and swap failed parts. When the workload grows, capacity is added without a new procurement round.

(08)Clients

What teams say after the first training run

We had H100 capacity running training jobs four days after the first call. Our previous vendor quoted eleven weeks for the same configuration.
DWDana WhitfieldVP Engineering, Helio Labs
Vorlixtech specified the fabric and storage properly, which is why our multi-node run scales instead of stalling. That advice was worth more than the hardware discount.
MIMarcus IyerHead of ML Platform, Meridian
One rate per station, no egress line items, and a human answers when a card throws errors at 2am. It is a boring relationship, which is exactly what we wanted.
PRPriya RamanCTO, Quantly

(09)FAQ

Questions we get on every scoping call

Something not covered here? Ask us directly — an engineer answers, usually the same day.

  • Configurations held in standing inventory — RTX 5090, RTX 4090, and H100 stations — are typically racked, imaged, and handed over within 48 hours. H200 and large multi-node clusters depend on current allocation; we give you a firm date on the scoping call.

(10)Get started

Tell us the workload. We will tell you the hardware.

Bring the model, batch size, and throughput target. On a 30-minute call you will get a configuration, a price, and an availability date — no pitch deck.

Office
10th Floor, 10055-106 Street NW, Edmonton, AB T5J 2Y2, Canada
Hours
Mon - Fri: 9:00 - 19:00 / Closed on Weekends

Request a configuration

We reply within one business day. Your details stay with us.