Services
Four services covering the whole arc: deciding what to build, deciding where it can safely run, building it, and proving it is controlled. Deployment runs from a UK cloud region through to fully air-gapped on your own accelerators. Most clients start with the first service and stop there until they are convinced.
A structured review of your data, systems, controls and people, ending in a ranked list of AI opportunities with costs, risks and a build order.
Full detailsOpen-weight models on your own infrastructure or in a UK region you control, up to fully air-gapped on NVIDIA DGX or HGX B300, hardened to DISA STIG and CIS Level 2.
Full detailsRetrieval over your documents, agents that complete real work, and automation wired into the systems you already run, built to be handed over, not rented back to you.
Full detailsThe policies, registers and evidence trail that let you say yes to AI, and prove to a regulator, auditor or procurement panel exactly how it is controlled.
Full detailsThe usual sequence
You do not need all four, and buying them as a bundle is usually a mistake. The common path looks like this.
Three weeks to establish what is worth building, what data it touches, and what the deployment constraint actually is. Frequently ends with a shorter list than you started with.
The data classification decides the architecture. For sensitive workloads that means private deployment; for low-classification work a hosted model under proper terms is often correct.
One well-chosen system, in production, measured against an evaluation set, handed over to your team. Not a platform, not a centre of excellence, just one working thing.
Policy, register, DPIA and evidence pack, so the second and third systems do not have to fight the same battle at the same meeting.
Governance often runs in parallel with the first build rather than after it: the evidence is cheaper to produce as a by-product of construction than to reconstruct later.
A 30-minute call, no pitch deck. Tell us what you are trying to do and we will tell you whether AI is the right tool, what it would take, and what it would cost, or that you should not bother.