We exist to give buyers, boards, and GRC officers the one thing they can't get from model providers: independent, adversarial AI risk intelligence — and an open exchange format that makes it comparable across your stack.
Enterprise AI adoption has outpaced governance infrastructure by years. Boards approve deployments they can't evaluate; M&A deals close on AI-heavy targets with no systematic way to quantify what's been acquired — or the liability that comes with it. Model cards and point-in-time audits describe. They don't measure.
We treat AI risk as a quantifiable, auditable property of the system under examination — a frozen score interface, a versioned engine, and improvements sold on demonstrated lift rather than promises. The party exposed to the risk pays for assessment; the published ranking is never for sale.
EU AI Act Article 9 and NIST AI RMF create obligations now. SEC disclosure rules add parallel pressure in the US. Boards need defensible structure, not aspirational policy.
Underwriters are actively looking for credible, furnished profiles to price and bind AI exposure. Better measurement is a precondition for a real market.
No common format for AI risk exists yet. Adopting one early means your tooling already speaks the format the ecosystem converges on — no rework later.
Principal · AI Risk Architect · Named Inventor
Two decades of enterprise systems architecture across fintech, regtech, and data infrastructure — including senior and VP-level roles at major data, payments, and identity/risk-data firms, and a named patent on distributed identity resolution (US 10,581,825).
The Shadow Simplex framework grew from a direct observation: the organizations best positioned to exploit AI were being handed almost no rigorous instrument to understand what they were taking on. It was built as a practical instrument for the people who live with the consequences — not abstract theory.
Start with a 30-minute scoping call. We'll tell you which SSS dimensions matter most for your situation and what an engagement would entail.
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