The ARC framework evaluates and optimizes AI brand visibility across three core pillars: Association measures how strongly models connect a brand to specific entities or queries in their parametric memory, while Relevance tests whether an AI will actively recommend that brand for a given topic. Complementing these memory-based signals, Citation audits which external source URLs and domains AI platforms retrieve and reference during live, grounded web searches.