AI that runs on your infrastructure, not someone else's
Private AI means running the model on infrastructure you control, your own servers or a UK or EU cloud, so your data is processed in-house and never sent to a third party's API. Self-hosted open models have caught up: for a great many business tasks, an open model running on your own hardware now does the job a commercial API would, without the data ever leaving the building.
For some businesses, the usual way of adding AI is a non-starter. Sending customer records, case files, or commercial data to an external API is a compliance problem, a confidentiality problem, or simply a risk you are not willing to take. The standard answer, use the big cloud AI and trust the contract, does not satisfy a regulator or a nervous client. Private AI removes the question by keeping the data where it already lives.
Why run AI privately
The case for private AI is rarely about the model and almost always about the data around it. These are the reasons businesses choose it.
Data never leaves
Sensitive records are processed on your infrastructure, so there is no third party to trust and nothing to leak in transit.
Compliance you can evidence
For regulated work in health, legal, or finance, "the data stayed on our servers" is an answer a regulator accepts.
No training on your data
Your information is never used to improve someone else's model, because it never reaches them in the first place.
Predictable cost
Your own hardware is a known, fixed cost rather than a per-call bill that climbs with every use.
The open models are good enough now
This used to be a painful trade-off: privacy or capability, pick one. That has changed. Open models you can run yourself now match the commercial APIs closely enough for most business tasks (extraction, drafting, classification, search over your own documents), on hardware that costs less than a single member of staff. We will tell you honestly where an open model is as good as the cloud one and where it is not, so the decision is made on facts rather than fear.
Privacy without the capability tax. Open models on your own hardware now handle most business AI tasks well, so keeping data in-house no longer means settling for less.
How it runs
Not everything needs to be private, so we start by separating what does from what does not. Often the right answer is a mix: private for the sensitive work, cloud for the rest.
Work out what needs to stay private
Which data and which tasks genuinely require it, because forcing everything in-house when it does not need to be just adds cost.
Choose the model and the hardware
The right open model for your tasks, and infrastructure sized to match, on your servers or a UK or EU cloud you control.
Build it into your systems
The AI features or agents you need, running against the private model, connected to your data with proper permissions.
Run and maintain it
Updates, monitoring, and model upgrades as better open models arrive, so it stays current without you having to mind it.
Who it is for
Private AI is worth the extra setup when the data genuinely cannot go to an external service.
Where it fits
Private AI is the "where" for the rest of our AI work: the AI features and AI agents we build can run against a private model just as well as a cloud one, so sensitive data stays put. It is the practical end of digital sovereignty: owning not just your software but the AI that reads your data, and the infrastructure it runs on.
Talk to us about private AI
Tell us what data you are working with and what is stopping you using AI today. We will give you an honest read on whether private AI is the answer. The first conversation is free, takes about thirty minutes, and comes with no obligation. Read more about what working with us looks like, or get in touch directly.
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