Private AI.
Your business, in control.
AI agents and trusted answers from your own data. Built to run in your cloud or on your premises, with access and sharing under your control.
Discuss private AIUseful AI. Clear boundaries.
Answers from private knowledge
Search contracts, technical records and internal guidance, with sources and access rules built in.
Agents with permission to act
Process documents and move work through your systems, with agreed limits and human approval points.
A system you can own
Replace a tool you no longer want to rent with a custom build you control, where it makes business sense.
The model can run
where you decide.
Open-weight models make their trained parameters available to download. We can use suitable releases to build AI on infrastructure you control, rather than relying on a public model service.
Llama
Mistral
GemmaWe choose the model for the task, not the logo. Quality, hardware needs and the licence for the exact release all matter.
Open-weight is not the same as open-source.
Availability of weights does not remove licence restrictions, reveal all training data or make a deployment private by default.
Private by design.
Not just by name.
We map where data goes, test one real workflow and agree what can leave the environment before scaling.
Your private cloud
Run in your cloud tenancy, with agreed regions, network controls, storage and access permissions.
On your premises
Host on your own hardware when data residency, connectivity or operational needs call for it. We assess capacity and maintenance with you.
Isolated environments
For stricter boundaries, we assess offline operation and restricted connections. Every dependency, update process and connected tool needs to fit.
Controls around the whole system
Access permissions, retention, logging, retrieval and agent tools all affect privacy. We document these choices and test against the agreed boundaries.
Private AI, explained.
What is private AI?
AI built to operate within an agreed environment, with controls over access, data processing and storage. We scope those boundaries around your business rather than assuming a public chatbot is the right fit.
What does open-weight mean?
The model's trained parameters are available to download. Suitable releases can run on infrastructure you control, subject to their licence. Open-weight does not automatically mean open-source, unrestricted commercial use or access to the original training data.
Does an open-weight model make our data private?
Not by itself. Privacy depends on hosting, network connections, logs, storage, permissions and any external tools the agent uses. We agree these controls before deployment and check the full data path.
Can it run without sending data to a model provider?
Yes, with a locally hosted model and a system designed without external model calls. For offline or isolated environments, we assess the hardware, model and connected tools needed to make that work.
Do we need to train a model on our data?
Often, no. Connecting a model to approved documents through retrieval can provide useful answers without retraining it. Fine-tuning is an option when testing shows a clear need for specialist language or task behaviour.
Is private AI cheaper or more accurate?
Neither is guaranteed. Hardware, hosting, maintenance and demand affect cost. We test candidate models on your actual work for answer quality, speed and running cost before recommending a deployment.
Who owns the finished system?
With Build & Own, you receive the custom code and documentation and deploy in an agreed private environment. The underlying model remains subject to its own licence. Managed Outcomes is also available, with agreed measures and delivery volumes.
What needs to stay private?
Tell us the task, the data and the boundaries. We will help scope a first build and agree how to measure it.