Private cloud vs on-premise AI: what each means, and which you need.

The two terms get used as if they were opposites, which is why people search for both “private cloud vs on-premise” and “on-premise private cloud”. They answer different questions. This page defines each one, compares them for AI specifically, and sets out when each is the right choice. Ermos offers both, so the comparison has no product to protect.

What a private cloud is

Most providers work from the US National Institute of Standards and Technology definition. A private cloud is cloud infrastructure provisioned for exclusive use by a single organisation. It may be owned, managed and operated by the organisation, a third party or some combination of them, and it may exist on or off premises (NIST SP 800-145).

So “private” describes who the infrastructure serves, and on its own says nothing about where it sits. A public cloud runs many customers on shared hardware, and you rent a slice of it. A private cloud gives one organisation its own environment, separated from everyone else’s. Providers differ in how far that separation goes: some dedicate physical hardware to you, others isolate you logically on shared equipment, and both are sold as private.

What on-premise means

On-premise, often shortened to on-prem, means the hardware sits inside your own building, on your own network. It describes location and nothing else: an on-premise system can be run by your own IT team or managed remotely by a provider. For AI, on-premise means the model runs on that hardware, so documents and questions are processed in the same building they already live in.

Two questions in one comparison

Most of the confusion clears once the two questions are separated:

An “off-premise private cloud” is the hosted version. An “on-premise private cloud” is dedicated infrastructure in your own building, run with the same self-service tooling a cloud provider would use. When people compare private cloud with on-premise, they almost always mean dedicated capacity in someone else’s data centre against hardware in their own office, and that is the comparison the rest of this page makes.

Private cloud vs on-premise for AI

AI adds a complication that general IT comparisons miss. Where your documents are stored and where questions about them are answered can be two different places. A private cloud can hold your files in Australia and still send each question, with excerpts from your documents, to a model hosted somewhere else. The comparison below keeps storage and processing apart for that reason.

When a private cloud is the right answer

• Your documents already live in the cloud. If your files sit in Microsoft 365 or Google Drive, putting AI hardware in the office does not change where those files are kept. A private AI instance in an Australian data centre can work from them where they are.
• Your team works across sites. Several offices, or staff working from home, all reach a hosted instance the same way.
• You have nowhere to put hardware. No server cupboard, a shared office, or a lease that makes installing equipment awkward.
• Your requirement is Australian handling. If clients or regulators ask that information stays in Australia, a hosted instance can satisfy that, provided every part of the service, including the model, operates in Australia.

When on-premise is the right answer

• Your policy or your clients require that information never leaves your building. Some engagement terms and internal policies are written that way, and only hardware on your premises meets them.
• Your most sensitive work. Privileged material, health records, and anything a client has asked to be handled with particular care.
• You want no outside dependency. An on-premise unit keeps working without an internet connection or a third-party provider.
• You want the system to learn from your work in private. On Ermos Dominion, ErmosIQ adapts the models to your business on your own machine.

Questions to ask any private cloud AI provider

How Ermos offers both

Ermos runs the same software two ways, and you can move from one to the other with your data.

Ermos Edge is the hosted private option. Each business gets its own instance in an Australian data centre. Your documents, the search index and your access boundaries stay on that instance. When someone asks a question, the question and only the excerpts that person is permitted to see go to an inference provider operating from a data centre in Australia. That provider is named in your agreement and contractually barred from keeping your content or training any model on it. Nothing is processed outside Australia, and Edge is live in days with no hardware.

Ermos Dominion is the on-premise option. An Ermos AI unit installed in your office: documents are indexed, searched and drafted from on the unit, and it can run with no internet connection at all. It adds ErmosIQ, which tunes the models to your business on your own machine.

Edge is a single monthly fee per business, with no setup fee and no hardware. Dominion is priced per unit, per month, sized to your business. Our on-premise vs cloud comparison sets both against the public and enterprise cloud options, and our provider checklist gives you the twelve questions to put to any vendor, including us.

Common questions