Service · Artificial intelligence

Cloud AI infrastructure

For organisations whose data must not go to a public AI service: healthcare, finance, the public sector and firms with valuable know-how. We build a closed environment in your own cloud account in an EU region, where the model runs and the data stays. You buy no hardware; we set everything up and operate it remotely.

Send an enquiry See the scope

EU region

data stays in the EU

GPU instances

sized to the model

Storage

for your datasets

Pay as you go

scale up or down

What the service covers

Requirements vary enormously: serving a ready-made model and training your own sit in completely different budget brackets.

Talk it through with us

Sizing

Which GPU type and how much video memory the model needs, and whether on-demand, reserved or spot capacity fits best.

Deployment

Open source models or managed model services set up in your own account in an EU region, with no data shared with the provider for training.

Storage

Object storage and a vector database for documents and training data, versioned, encrypted and backed up.

Isolation

A private network with no public endpoint, access managed through Entra ID and every call logged.

Monitoring and cost

GPU utilisation, latency, queue length and budget alerts, so a forgotten instance never runs up a fortune.

Documentation

Data flows and locations described for your GDPR records and for AI Act requirements.

How we deliver it

A ready-made model can be live in the cloud within days. An environment for fine-tuning or training takes a few weeks, depending on data volume and GPU quotas at the cloud provider.

Requirements

Which model and size, expected request volume, and whether fine-tuning on your own data is needed.

Estimate

Architecture and a monthly budget with a frank comparison of cloud providers and pricing models.

Build

Environment defined as code, model deployed and connected to your systems.

Handover

Documentation, monitoring and a walkthrough for your IT staff, or ongoing operation by us.

GPU hardware ages faster than ordinary servers. A new generation arrives roughly every two years, and whatever you buy today will be far slower than the latest kit three years from now. Renting capacity in the cloud means moving to newer GPUs is a configuration change, and you pay only for the hours the model actually runs.

Common questions

Yes, if the data is not sensitive and a business agreement with EU data processing is available. A private environment makes sense when legal or commercial reasons mean the information must not leave your control.

Model size decides it: the model has to fit in video memory, so that figure comes first. For everyday text tasks a mid-range GPU is enough, and the top tier is rarely necessary.

For summarising documents, searching a knowledge base, sorting enquiries and helping with correspondence, generally yes. For complex multi-step reasoning the largest commercial models still have the edge. Test on your own material before committing.

That depends on GPU type and the number of hours the model runs. We give you a monthly estimate up front, set budget alerts and can switch instances off outside working hours.

Related services

View the whole area

Service AI implementation Practical use cases with a measurable return, not experiments Service AI strategy Roadmap, readiness check and a clear view of the AI Act Service AI training for staff Hands-on training built on your own everyday tasks

Let us build your AI environment

Describe the task and the data that must stay under your control. We will propose an architecture in an EU region with a monthly budget.

Email
office@apply.dk

Coverage
All of Denmark, delivered remotely

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