HyperAI

HyperAI provides enterprise NVIDIA GPU infrastructure for AI teams needing dedicated compute for training, fine-tuning and inference, with single-tenant deployment, Amsterdam hosting and named engineering support.

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Enterprise GPU infrastructure for AI

HyperAI is an enterprise GPU infrastructure service for AI teams that need dedicated NVIDIA compute rather than shared cloud instances. The site presents it as production-grade infrastructure for training, fine-tuning, and inference, with hardware options spanning A100, L4, RTX 6000 Pro, and H200.

Its public pages emphasize procurement-friendly deployment options: single-tenant nodes or isolated clusters, SLA-backed uptime, named engineering support, and reserved capacity contracts. Every tier includes a managed infrastructure baseline in an Amsterdam Tier III+ datacenter with 10 Gbps networking and local NVMe storage.

Core capabilities

Multiple NVIDIA GPU families

HyperAI offers A100, L4, RTX 6000 Pro and H200 GPU configurations so teams can choose hardware aligned to training, inference or larger context windows.

Dedicated tenancy

The homepage describes single-tenant nodes and isolated clusters, which is aimed at environments that need dedicated compute without sharing nodes with other customers.

Managed datacenter and networking

Each deployment includes a Tier III+ Amsterdam datacenter, 10 Gbps vPort, and unmetered traffic with fair-use terms, giving the service a fixed infrastructure baseline.

Sized CPU, RAM, and storage tiers

Configurations pair the GPU with AMD EPYC processors, NVMe storage, and defined RAM and vCPU tiers, allowing deployments to be sized to workload requirements.

Reserved capacity contracts

The site states that reserved capacity is available through annual and multi-year contracts with guaranteed allocation and fixed pricing on request.

Named engineering support

HyperAI includes named technical support, with a dedicated technical account manager and 24/7 on-call engineers rather than a generic ticket queue.

Common workloads

Model training and fine-tuning
Use the A100 and H200 configurations for memory-hungry training, fine-tuning, and frontier LLM work where NVLink or HBM capacity matters.
Inference serving
Use L4 for production inference workloads such as chatbots, embeddings, and video pipelines when energy efficiency and right-sized GPU capacity matter.
Large-context single-node workloads
Use RTX 6000 Pro for large-context inference or dense single-node training when you want a Blackwell-class GPU with 96 GB of memory.
Reserved enterprise capacity
Use the dedicated tenancy and isolated cluster model for organizations that want reserved GPU capacity, fixed pricing on request, and procurement-friendly contracts.
Production AI operations
Use the Amsterdam-based infrastructure and named support model for teams that need a managed deployment with clear operational ownership.

Pros and Cons

Pros

Multiple NVIDIA GPU options cover different workload profiles, from L4 inference to H200 frontier training.
Dedicated tenancy and isolated clusters are positioned for teams that need non-shared compute.
Each deployment includes a clear infrastructure baseline: Tier III+ Amsterdam hosting, 10 Gbps network, NVMe storage, and AMD EPYC CPUs.
The site states a 99.9% uptime commitment with service credits and transparent incident reporting.
Support includes a named technical account manager and 24/7 on-call engineers.

Cons

The public site does not expose a working pricing page; current pricing is shown on the homepage instead.
Software integrations, APIs, and onboarding workflow details are not documented on the pages provided.
Pricing is quoted per month with VAT excluded, and annual or multi-year discount terms are only available on request.

FAQ

What is HyperAI used for?

HyperAI is a managed enterprise GPU infrastructure service for AI workloads. The homepage positions it for training, fine-tuning and inference on NVIDIA GPUs, with workloads split across A100, L4, RTX 6000 Pro and H200 configurations.

How is HyperAI provisioned?

The site shows dedicated single-tenant nodes and isolated clusters, but it does not document self-service setup steps. The public pages present a sales-led procurement flow with platform and spec-sheet links rather than a documented onboarding wizard.

What infrastructure comes with each deployment?

HyperAI lists baseline infrastructure such as a Tier III+ Amsterdam datacenter, 10 Gbps unmetered network, NVMe storage and AMD EPYC CPUs matched to each GPU. Specific software integrations or orchestration tools are not described on the public pages provided.

What support and uptime commitment does HyperAI offer?

The homepage says each deployment includes named engineering support, including a dedicated technical account manager and 24/7 on-call engineers. It also mentions SLA-backed uptime with a 99.9% availability commitment and service credits.

Is there published pricing?

The public site does not show a verified pricing page. The homepage lists monthly starting prices for each GPU configuration and notes that annual and multi-year discounts are available on request, with VAT excluded.

Quick Facts

Category: Enterprise GPU infrastructure
Primary GPUs: A100, L4, RTX 6000 Pro, H200
Hosting location: Tier III+ datacenter in Amsterdam, Netherlands
Network: 10 Gbps vPort, unmetered traffic with fair use
Support: Named technical account manager and 24/7 on-call engineers
Pricing signal: Monthly pricing shown on site; pricing page at /pricing returns 404