Cloud vs. On-Premises AI

Where should your AI platform run? This guide compares cloud, private cloud and on-premises along data sovereignty, compliance, cost, latency and operating effort.

  • Public cloud: fastest start, shared responsibility for data location
  • Private cloud: dedicated tenancy in an EU data centre
  • On-premises: full control, no external data flow
  • Hybrid: sensitive retrieval on-premises, non-sensitive bursts in the cloud
  • U-KNOW runs identically in both models: managed service or U-KNOW Hub on-premises

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  • What matters is not where the servers are, but who can legally compel access.
  • The break-even between cloud and own hardware is driven by GPU utilisation and query volume.
  • The EU AI Act regulates risk, transparency and documentation, not the hosting location.

FAQ

Is on-premises AI more secure than cloud AI?

On-premises removes external data flow entirely. A certified EU private cloud reaches a comparable protection level for most enterprise workloads, provided the operator is not subject to third-country access laws.

What does on-premises AI cost compared to cloud?

On-premises requires hardware and operating staff up front but delivers a stable cost per query. Cloud avoids the investment and scales elastically.

Can we start in the cloud and move on-premises later?

Yes. With U-KNOW the same Enterprise OS is deployed as a managed service or via the U-KNOW Hub in your own data centre, so applications and permissions carry over.

Does the EU AI Act require on-premises operation?

No. The EU AI Act regulates risk classification, transparency, human oversight and documentation, not the hosting location.

What about self-hosted LLMs?

Self-hosted or distilled models run on your own GPU resources and are the usual choice when prompts must never leave the network.