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Business AI: on-premise, cloud or hybrid

AI can be run in different ways. The task decides.

On-premise, in the cloud or a combination. We help you choose the path that fits your task.

What do you want to do?

Five starting situations.

I want to try AI.

We validate one specific task in a test environment.

I want to develop or test my own models and applications.

A compact AI workstation is often enough for development and validation.

I want to use AI on company data.

First we clarify which data, who may access it and where it will be processed.

I need to prepare production AI infrastructure.

We design the infrastructure as a whole – including power, cooling and management.

I need to compare running it ourselves with the cloud.

We assess the economics individually, usually over a three-year horizon.

On-premise AI versus cloud

No option isbetter by default.

CriterionOn-premiseCloud serviceHybrid model
DataProcessed in your environment, under your control.Processed by the provider under its terms and settings.Sensitive workloads on-premise, the rest in the cloud.
CostsHigher initial investment, more predictable operation.Low entry cost, pay per use or per user.A combination of both models.
ResponsibilityAdministration, security, capacity and maintenance are on you or your supplier.The provider manages the infrastructure.Roles need to be clearly divided.
When it makes senseSensitive data, steady load, need for your own tuning.Quick start, variable usage, broad tooling.Different workloads with different data requirements.
Technology

What your AIcan run on.

We choose hardware based on the task.

For development and testing

Compact AI workstation

Model to be confirmed

NVIDIA GB10 platform for developing and validating workloads.

For example
Dell Pro Max with GB10 (exact model to be confirmed)
For more demanding workloads

Custom AI infrastructure

Coming soon

A smaller rack for more demanding workloads. In development – we will publish specifications once confirmed.

Illustrations, not product photos.

What running it yourself involves

What you need tothink about upfront.

Capacity limits

How many users and models the device can handle.

Expert administration

Who takes care of updates and monitoring.

Security

Access rights and usage rules.

Validate AI on your own task.

A pilot doesn’t have to lead to buying infrastructure.

2 minutes, no obligation

Try AI for our company