On Premise AI
AI that runs on infrastructure the organisation itself owns and maintains, rather than on a cloud platform run by a provider. Its cost is front-loaded into hardware, licensing and the staff to run it, and it keeps processing under the organisation's direct control.
What it means in practice
The cloud and on-premise comparison describes the two cost shapes: cloud cost scales with usage and starts small, while on-premise cost is front-loaded and falls per unit of use once volume is high and steady. Capacity behaves differently too. Cloud adds it on demand; on-premise adds it by ordering and installing more. The local LLM review adds what running a model in-house actually requires: GPU infrastructure sized to the model, and an ongoing ML-ops capability to keep it patched, scaled and monitored.
How we use it
Both reviews treat it as a choice made workload by workload, not once for the whole organisation. A hybrid setup, with sensitive or regulated work kept in-house and less sensitive tasks sent to a hosted model, is described as a standing third option. The comparison says the decision should be made against documented requirements for data residency, latency and volume.
FAQ
Questions about on premise AI
Is On-Premise AI more Secure than Cloud AI?
Not automatically. The cloud and on-premise comparison says on-premise removes one layer of trust in a third party, but security then depends entirely on how well the organisation runs its own systems.
Does running a Model locally make it GDPR or EU AI Act Compliant?
No. Both attach to what the system does and what data it processes, not to where it runs. The local LLM review notes that a poorly governed local deployment can breach either as easily as a hosted one.
What it means for a Business
What on-premise buys is direct, demonstrable control over where data physically sits and who can reach it. That matters most where data residency, a contractual restriction or an internal security policy rules out sending information outside the organisation's own network at all.
Ready to put this to work?
Tell us where your team is with AI and we will tell you honestly what would make the biggest difference.