Definition
Private AI
Running AI without your data ever leaving your perimeter, what makes AI "private", and how to deploy it.
By James Drayson
In short
Private AI is artificial intelligence that runs inside your own perimeter with no external data sharing or telemetry, so prompts, documents, and outputs never leave your environment. Unlike public AI services, a private deployment keeps your data, and ideally the model, under your control.
What makes AI "private"?
- In-perimeter inference: The model runs on infrastructure you control, not a shared external service.
- No external telemetry: Nothing is logged or sent to a third party, and your data is never used to train someone else's model.
- Owned model (ideally): True privacy is strongest when you also hold the weights, so there's no dependency on a vendor's terms.
Private AI vs public APIs
Public AI APIs are convenient but send your prompts and documents to the provider, governed by their terms and sub-processors. Private AI inverts this: the data stays with you, which is essential for regulated, confidential, or proprietary work.
How Locai delivers private AI
Locai gives you a model you own, post-trained on your data and deployed inside your perimeter, on-prem with Locai One, in your cloud tenant, air-gapped, or in a UK sovereign cloud. Every inference runs locally, so privacy is structural, not a setting.
What this looks like with Locai
Running AI locally means assembling hardware, a model and a serving stack that work together. Here is what it looks like when that arrives as one product.
Locai Labs builds Locai One, an on-prem AI appliance. It is one machine that arrives with everything already in it: the hardware, our open-weight Locai Juno models, and Locai OS, the operating system that serves the models and handles users, access and monitoring. You plug it into a mains socket and your network, and your team is working in about 15 minutes. No cloud account, no per-token bill, and nothing leaving the building.
The reason a data-centre-class model fits in a box on your floor is SPACE, our compression algorithm. Instead of asking how much of a model can be cut while keeping it broadly similar, SPACE asks what the model needs to be good at, preserves the subnetworks behind those capabilities and strips back the rest. The result is a smaller specialist rather than a shrunken generalist, tuned to the exact hardware it ships on.
Locai One starts at £29,950 for a team, and Locai One Pro at £49,950 for an organisation, bought once and owned outright. Both run air-cooled on standard mains power and work fully air-gapped. Any compatible open-weight model runs alongside Juno, and if you need a model trained on your own proprietary data we can post-train one and deploy it on the same machine.
Frequently asked questions
What is private AI?
AI that runs inside your perimeter with no external data sharing, so prompts and documents never leave your environment.
Is ChatGPT private?
The public ChatGPT service sends your inputs to OpenAI's servers under their terms. That is not private AI in the in-perimeter sense; a private deployment keeps data inside your environment.
How do I run AI privately?
Deploy a model you control inside your own infrastructure, on-prem, air-gapped, or in your cloud tenant. Locai One packages this as a turnkey appliance.
Is private AI secure?
Keeping inference in-perimeter removes a major attack and exposure surface. Combined with owned weights and ISO 27001-aligned deployment, it is the strongest posture for sensitive data.
Book a sovereign AI briefing
A 30-minute session on owning your model: deployment options, the data path, and a clear cost range for your use case.