We are the AI control firm for the institutions that steward the world's capital.

Most of the conversation about AI in finance is about governance — the policies, frameworks, and committees that describe what an institution intends to do. That work matters. It is also not control. Control is what an institution can prove it does: technical, demonstrable, on demand, to a regulator or a fiduciary.

We exist to close that gap. And in financial services, closing it means working in two dimensions at once.

Deep — across the full stack. The AI an institution relies on runs on five ecosystems: power, compute, data centers, models, and agents. Control of any one in isolation is not control of the whole. We work down the entire stack, not the application layer where most governance stops.

Wide — across the full chain. A financial institution rarely operates the AI it depends on. It runs inside the managers, servicers, and providers the institution delegates to — firms it does not own and cannot directly audit, producing the numbers it nonetheless books and answers for. Control that stops at an institution's own perimeter stops short of its duty. We work across the delegation chain, not just inside one firm's walls.

Deep and wide together is the whole problem. It is also why the firms institutions have historically turned to do not fit. Consultancies sell advice. Software vendors sell access, not ownership. Systems integrators build to spec without designing the control architecture itself. And the hyperscalers and model vendors sit inside the chain as counterparties — they cannot be the neutral party that verifies it.

Institutional AI is built differently, and on purpose. We hold no hyperscaler alliance, no model-vendor partnership, and no resale economics with any infrastructure provider. We answer to one party: the institution that must command its intelligence.

AI is a given. Control is not.™

Institutional AI

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Institutional AI

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