Structured Disagreement as an Architecture for Multi-Model AI

This article presents xCheckAi, a structured, multi-model comparative framework designed to resist oracle-like use of large language models in consequential decision contexts. Rather than producing a single synthesised answer or enforcing consensus, the framework exposes agreement, disagreement, uncertainty, and refusal across independently queried models, preserving provenance and auditability at each stage. The system is intentionally non-prescriptive and does not determine truth or recommend actions; instead, it functions as epistemic infrastructure aimed at preserving human responsibility and preventing the quiet transfer of judgement to AI systems.