Organizations are deploying AI agents into governance-critical processes — procurement, risk decisions, compliance enforcement, architectural change. The gap between what these agents can do and what governance can verify is widening. That gap is where catastrophic failures live — not because the AI is wrong, but because governance can't tell whether it's right.

We built OntoRamp on a bet: governance is not a compliance problem — it is a physics problem. Organizational intent degrades through transformation the same way energy dissipates through friction. Policies exist but nothing connects them to the decisions they're supposed to govern. Accountability is declared but structurally unenforced. These aren't failures of discipline. They're structural gaps that only a graph can see.

The pages below are the published specification of a computable governance system — the theoretical framework, the measurement vocabulary, the domains we assess, the methodology we follow, and the API that makes it programmable. Written for governance architects, platform engineers, and executives who need precision, not persuasion.