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Why AI Control Tower

Five categories, and the gaps between them

LLM gateways route requests. Observability and FinOps tools report cost after it is incurred. IT governance platforms hold the policy but sit outside the request. AI security tools inspect traffic for threats rather than for spend. Sovereign clouds solve where it runs, not what runs there.

Each is good at its own job, and most enterprises will own two or three of them. None carries a single request from the policy decision through to the line on the provider invoice.

CapabilityLLM gatewaysObservability & FinOpsIT governanceAI securitySovereign cloudsAI Control Tower
Sits in the request path, enforcing in real time~
Cost observability & attribution~~
Model routing & optimisation
Department / project budget allocation & reconciled billing~
UK-hosted, self-contained deployment~~
Designed for this ~Partly, or via integration Not what the category is for

Categories, not products. Any given vendor may do more than its category suggests, so bring your actual shortlist to a call and we’ll go through it properly.

Our approach

Where it differs

Technical control and financial control belong in the same layer, because they describe the same request. The five decisions below follow from that.

One product, not an integration project

Assembling this from three or four of the categories above is possible. It is also a programme of work, and it leaves you owning the joins between them.

Accountability Finance can rely on

Cost tools model AI spend from usage exports. This settles it against the vendor invoice, so Finance is working from billed reality.

In-path governance

Observability tells you what happened. Enforcement happens as the request is made, so a breach of policy or budget is prevented rather than reported.

Not a US-hosted default

The best-known tools in these categories are US-based, and UK deployment tends to be an option rather than the default. Here it is the starting assumption. See the deployment patterns

Multi-provider neutrality

Designed to work across the major model providers, alongside self-hosted models, so governance is not tied to one vendor’s roadmap.

Compare us against what you are already considering

Bring the tools you already run, or the shortlist you are working from. We’ll be straight about where AI Control Tower overlaps them and where it does not.

Talk it through with us