Typical trigger
AI infrastructure for sensitive data, latency and operating constraints.
We determine whether private AI infrastructure is appropriate for your use case and which data, security and operational questions need to be resolved first.
Infrastructure
Private AI Infrastructure
We assess whether a private cloud, a European provider or on-premises infrastructure best fits your data, security requirements and operating constraints.
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Signal
Public cloud is excluded
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Risk
Operations unclear after PoC
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Guardrail
Operating model with real numbers
Situation
When this becomes relevant
Public AI services are not suitable for every type of data or process. Privacy requirements, contracts, latency or ongoing costs may call for private infrastructure. The key questions are which operating model is realistic and what it will require beyond the hardware.
Which data must be processed privately, and where would an external service with appropriate safeguards be sufficient?
What ongoing costs arise beyond the hardware, including patching, monitoring and model updates?
Would a European cloud provider meet the requirements, or do the constraints require infrastructure under your own control?
Risks
Risks to address
On-premises infrastructure without clear ownership for secure and reliable operation.
Investment in GPU capacity before workloads, expected utilisation and future scaling needs are understood.
Assuming that privacy requirements always demand on-premises operation without assessing alternative safeguards.
Which infrastructure model fits your AI workloads?
Describe the data involved, your requirements and the current environment. We will compare suitable operating models and include ongoing costs in the assessment.