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GPU Infrastructure for Cloud Operators.

Aurora supplies, provisions, and operates GPU clusters for neoclouds, GPU platforms, and AI service providers.
White-label ready. Your site or ours. No CAPEX required.

Reserve GPUs
Aurora Infra Owned Data Center GPU Capacity
Owned data centers
We control the real estate.
Aurora Infra Direct Procurement
Direct OEM procurement
No broker, no waitlist risk.
Aurora Infra Managed Kubernetes
Full-stack managed ops
Rack to Kubernetes, operated.

Running a GPU Cloud Requires More Than GPUs...

Building GPU infrastructure for your customers means solving more than hardware procurement. It means InfiniBand networking, Kubernetes with GPU-aware scheduling, storage that keeps GPUs fed, multi-tenant isolation, GPU health monitoring, and the operational team to maintain utilization above 80%.

Most GPU platform operators spend more engineering time keeping infrastructure alive than building the product their customers actually pay for.

Aurora solves this by deploying and operating the complete GPU infrastructure stack — from power and cooling to Kubernetes handoff and inference endpoints — so you can focus on your customers, not your hardware.

8-16 Weeks typical deployment lead time
99.9% Platform uptime SLA
0 Hardware capex required

A Complete GPU Infrastructure Stack,
Deployed and Operated.

Hardware Procurement and Provisioning

Aurora procures B200 and B300 hardware through direct OEM relationships — not secondary markets or brokers. Rack-and-stack, InfiniBand networking, and Kubernetes handoff delivered as a fully managed service. 16 to 1,000+ nodes per deployment.

Managed Kubernetes with GPU Scheduling

GPU-aware Kubernetes orchestration included in every deployment. NVIDIA GPU Operator, multi-tenant namespace isolation, per-tenant GPU quotas, and continuous GPU health monitoring. Workloads scheduled to the right hardware automatically.

White-Label Ready Platform

Every customer-facing layer carries your brand. The Aurora Console white-labeled under your domain and logo. Billing, API endpoints, and portal — all yours. Aurora operates behind it, invisible to your customers.

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AI-Optimized Storage

GPU-aware tiered storage integrated into every cluster via RDMA and GPUDirect Storage. NVMe hot tier for model weights and active training data. HDD capacity tier for checkpoints, datasets, and archives. S3-compatible API. 60–70% cheaper than all-flash at equivalent GPU throughput.

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Inference Endpoints

Turn GPU capacity into metered inference revenue. OpenAI-compatible endpoints for open-weight models, billed per token. Aurora handles model optimization, serving infrastructure, scaling, and per-token metering.

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No CAPEX Required

Aurora structures GPU infrastructure as pure operating expense. No hardware purchase, no depreciation schedule, no balance sheet impact. Preserves your capital for product development and customer acquisition while your GPU offering scales.

Platform Specifications

TECHNICAL REFERENCE
GPU Hardware NVIDIA B200 (192GB HBM3e), NVIDIA B300 (288GB HBM3e)
Cluster Size 16 to 1,000+ nodes
Interconnect 800G InfiniBand XDR
Network Topology Non-blocking Spine-Leaf
Power per Rack ~40 kW (B200), ~45 kW (B300)
Kubernetes Managed, GPU topology-aware scheduling, NVIDIA GPU Operator
Multi-Tenancy Namespace isolation, per-tenant GPU quotas and monitoring
Storage NVMe hot tier + HDD capacity tier, S3-compatible, RDMA/GPUDirect
Inference OpenAI-compatible API, per-token metering, open-weight model catalog
White-Label Console, portal, domain, billing, API endpoints
Confidential Compute Hardware TEE on B200 and B300
Deployment Lead Time 2–6 weeks (Aurora sites). Customer-hosted timelines vary.
SLA 99.9% platform uptime
Pricing Quote-based. Contact sales for configuration and commercial terms.

Built for GPU Cloud Operators

GPU Cloud Platforms

Companies building hosted GPU compute services who need infrastructure supply and operations without owning hardware. Aurora provides the complete managed stack — white-labeled and ready for downstream customers.

AI Inference Providers

Companies offering AI inference APIs who need reliable, dedicated GPU infrastructure. Aurora delivers private inference endpoints with per-token metering, model optimization, and serving infrastructure.

Cloud and MSP Partners

Managed service providers adding GPU compute to their service portfolio. Aurora handles procurement, deployment, and ongoing operations. Partners own the customer relationship and set their own pricing.

Neoclouds Scaling Fast

GPU platform operators who have outgrown their current supply arrangements or need additional geographic coverage. Aurora provides dedicated hardware allocation through direct OEM procurement relationships.

Supply Certainty In a Market That Doesn't Have It.

Owned Data Centers

Aurora owns data centers and rack space across North America, Western Europe, the Nordics, GCC, and APAC. When Aurora quotes a GPU deployment, the commitment is backed by real estate Aurora controls, not a third-party allocation we're waiting on.

Direct OEM Procurement

Aurora procures B200 and B300 hardware direct from NVIDIA. No broker margins, no secondary market uncertainty, no supply chain surprises between your commitment and your customers' expectations.

Capital-Backed Delivery

Aurora's access to capital means we move at the speed of your roadmap. We structure deployments as operating expense — no hardware purchase on your balance sheet — while absorbing the capital requirements of the deployment on our side.

Reserve GPU Infrastructure

GLOBAL DEPLOYMENT

AI Data center infrastructure.
Deployed close to where you operate.

Aurora builds and operates AI data center capacity across North America, Western Europe, the Nordics, GCC, and APAC.

Visit Aurora Infra's main website... -->