Reality-Graded Upgrade Gate for Structured AI Workflows

A private evaluation service and buyer-owned software package for teams running production AI workflows that already have objective labels or fast-resolving outcomes, such as document extraction, classification, routing, eligibility checks, and policy enforcement. Instead of trying to judge subjective text quality, the product builds a regression harness from real historical failures and labeled cases, runs adversarial multi-model debate on candidate outputs, and issues a compact release decision: promote, demote, hold, or kill. Regressions are tagged with AE's autopsy patterns so teams can see whether a change failed through grounding loss, premise-conclusion severing, concession laundering, cosmetic confidence, epistemological shielding, or temporal/transmission blindness. The buyer owns the evaluation asset in portable flat files/Supabase, making it a narrow, high-signal upgrade gate for objective AI tasks rather than a general enterprise eval platform.

As enterprises move from chatbots to production AI workflows, a private, reality-graded upgrade gate for objectively measurable tasks is a focused, credible, and monetizable wedge.

Commander override: DEFER. Deferred 30 days (revisit 2026-05-18). Contradiction scan flagged 2 load-bearing issues — most importantly: the 6-pattern autopsy was validated on predictive/subjective reasoning, NOT objective release decisions with ground truth. The dossier's core wedge claim is unvalidated. Pattern sweep identified this as the 'private-data evaluator' gravity well the engine needs to escape. Revisit only if an honest-fit test (debate vs. regression baseline on one real labeled dataset, ~5-10h build) is comple