Executive Summary

Runcible qualifies AI for institutional work.

Runcible is the semantic compiler and qualification runtime for institutional AI – where correctness, testifiability, ethics, possibility, warrantability and liability are demanded.

Foundation models can draft, summarize, classify, retrieve, compare, recommend, and propose. But institutions cannot act on fluent output alone. Before AI-mediated work can enter law, healthcare, finance, insurance, government, defense, or enterprise operations, the institution must know: What role was the AI playing? What evidence did it use? What rules applied? What authority governed the work? What failed? What must escalate? What record remains?

Runcible supplies the missing qualification control plane between foundation-model generation and institutional execution.

Runcible translates candidate language into operational claims, then applies universal admissibility tests — testifiability, reciprocity, possibility, authority, and bounded liability — and then applies the institution’s local law, policy, contract, workflow, evidence standard, and escalation rules.

The result is not merely an answer. The result is a Decidability Record: a reviewable, auditable, certifiable record showing what was qualified, what failed, what was repaired, what must escalate, and what remains undecidable.

Runcible does not compete with foundation models. It qualifies their outputs.

It is not a wrapper, guardrail, compliance checklist, eval system, or governance dashboard. Commercially, Runcible appears as a governance layer. Technically, it is a semantic compiler and qualification runtime that lets AI-mediated work become admissible for institutional action.

Runcible unlocks high-liability AI by making institutional use testable, reviewable, auditable, certifiable, and liability-bounded.

We are not building another AI.

We qualify AI for institutional work.