What is Aurora's private AI infrastructure platform?

Aurora is a full-stack private AI infrastructure platform built for enterprises, telcos, and governments that need control over their compute, data, costs, and operations. It spans five integrated product areas: Compute, GPU and AI, Storage, Network, and Data Centers. Each product is independently deployable and integrates across the full Aurora stack. Aurora operates the infrastructure — customers and partners control the brand, pricing, and customer relationships.

How does Aurora compare to hyperscalers like AWS, GCP, and Azure?

Aurora delivers private AI infrastructure at 50 to 80 percent lower cost than hyperscalers. GPU pricing runs 2 to 7 times below AWS, GCP, and Azure rates. Aurora does not charge egress fees. Data stays in-region by default, which hyperscaler architectures cannot guarantee. Aurora is deployed under the customer's or partner's control — there is no shared public infrastructure, no data routing through third-party networks, and no vendor lock-in.

What deployment models does Aurora support?

Aurora supports three deployment models. Aurora AI Platform deploys on the customer's existing hardware. Managed Cloud deploys on Aurora-owned hardware. Private AI IaaS covers new infrastructure builds from the ground up. All three models use the same Aurora platform, the same management layer, and the same 99.9% uptime SLA. Deployments go live in 1 to 8 weeks depending on the model and scope.

Can Aurora's platform be white-labeled and resold?

Yes. Aurora's full platform is available as a white-labeled service for telcos, MSPs, and regional operators. Partners present the infrastructure under their own brand — their logo, their domain, their billing, and their customer relationships. Aurora operates the infrastructure and remains invisible to the end customer. Resellers typically earn margin on compute, GPU, and storage services priced against Aurora's wholesale rates.

What regions does Aurora operate in?

Aurora is active across the Americas, Nordics, UAE, and APAC. Engagements are delivered directly or in collaboration with local operators, depending on regulatory, geographic, and operational requirements. Aurora deploys in-region — data stays within the target jurisdiction by default.

What performance benchmarks does Aurora's platform deliver?

Aurora's platform delivers 98.5% cluster goodput, 11 or more GB per second storage throughput, 3.2 Tbps InfiniBand fabric for GPU interconnect, and a 99.9% platform uptime SLA across all deployment models.

Who is Aurora's infrastructure built for?

Aurora builds for three types of organizations. Enterprises and public sector organizations that need private AI infrastructure for their own operations — in-region, under their control, without hyperscaler dependency. Telcos, MSPs, and regional operators who white-label and resell private AI services under their own brand. Channel and GTM partners such as system integrators and distributors who introduce Aurora into enterprise accounts and own the customer relationship.

Aurora AI Cloud: Private, Sovereign AI Infrastructure

The cloud you rent today was not built for the way AI runs.

Compute is priced around the vendor's economics. Storage is cheap to fill and expensive to use. And every time your data moves to the GPUs that need it, egress fees turn your own AI into a metered expense. The larger your datasets and GPU footprint get, the worse the economics get, and the harder it becomes to leave.

There is a second cost that never shows up on the invoice: your data lives in someone else's jurisdiction, on someone else's terms. For regulated work, sovereign deployments, or anything you would not want leaving your region, that is a question of control.

The Aurora AI Cloud answers both on one platform: private compute, GPU clusters, and S3-compatible storage, deployed in your region, under your control, operated by us. You keep the data, the jurisdiction, and the economics.

Storage, compute, and GPU built to work together.

Aurora AI Cloud is one platform with a single management layer. You log into one console and see it all: dashboard, storage buckets, credentials, virtual machines, networks, volumes, and an event log. Provision a GPU-aware cluster and the object storage that feeds it from the same place, and they connect on one network and one bill.

That is what running a cloud looks like. Workloads land on the right GPU. Datasets stay next to the compute that needs them. Nothing leaves your region unless you send it.

aurora-ai-cloud-console-object-storage-dashboard

What can you run on Aurora AI Cloud?

Inference

Private, in-region model serving.
Run open-weight and private models on dedicated capacity, without routing your prompts or data through someone else's cloud.

Explore Aurora Inference

Compute

VMs, managed Kubernetes, dedicated instances.
Private compute for AI workloads, with GPU-aware Kubernetes scheduling and single-tenant hardware where you need isolation. Deployed under your control, operated by Aurora.

Explore Aurora Compute

Storage

S3-compatible object storage. PiB-scale hot and archive storage with full AWS S3 API compatibility and no egress fees. Drop-in for most S3 workflows with no code changes. $5.99 per TiB per month, start with 1 TiB free.

Explore Aurora Storage

GPU

Dedicated GPU capacity, turnkey or bespoke.
The physical infra side of Aurora: managed clusters deployed into ready capacity, or a custom, MW-scale data-center buildout.

Explore Aurora GPU

Where does your data live?

You choose the region. Aurora keeps it there, and gives you the controls to prove it.
Together, these make Aurora a sovereign cloud you can run in the jurisdiction your work requires.

Residency

Your data and workloads stay pinned to the region you choose, enforced at the infrastructure layer.

Sovereignty

Deployment inside a single jurisdiction, with operations and data access scoped to it.

Air-gap

Physically or logically isolated environments for your most sensitive and classified workloads.

Standard on every Aurora deployment.

Every Aurora AI Cloud deployment ships on the same foundation, whichever capabilities you run.

Security & Compliance

Encryption in transit and at rest, with bring-your-own-KMS
Immutable WORM backup with configurable retention
Private networking: VPC, firewall, and security groups

Data &
Region

S3-compatible storage with no egress fees
In-region and sovereign deployment, air-gap available

Operations

Managed Kubernetes with GPU-aware scheduling
99.9% uptime SLA, Aurora operates what it deploys
Full console and API access

ALSO AVAILABLE: WHITE-LABEL

Your brand on the console. Your customers. Your margin.

Aurora AI Cloud is available as a fully white-labeled service for neoclouds, telcos, MSPs, and regional operators. Your customers get private compute, GPU instances, and S3-compatible storage under your logo, your domain, and your pricing. Aurora operates the infrastructure and stays invisible across portal, billing, and API endpoints. You own the customer relationship.

Building a cloud to resell? Aurora white-labels the full stack under your brand, domain, and pricing.

Learn about the Aurora Partner Program

One Private Cloud for AI

The cloud you rent today was not built for the way AI runs.

Storage, compute, and GPU built to work together.

What can you run on Aurora AI Cloud?

Inference

Compute

Storage

GPU

Where does your data live?

Standard on every Aurora deployment.

Security & Compliance

Data &
Region

Operations

Your brand on the console. Your customers. Your margin.

Start in minutes, or scope a deployment.

One Private Cloud for AI

The cloud you rent today was not built for the way AI runs.

Storage, compute, and GPU built to work together.

What can you run on Aurora AI Cloud?

Inference

Compute

Storage

GPU

Where does your data live?

Standard on every Aurora deployment.

Security & Compliance

Data &Region

Operations

Your brand on the console. Your customers. Your margin.

Start in minutes, or scope a deployment.

Data &
Region