Relevance evaluates direct model recommendations by executing binary yes/no recommendation probes across multiple active LLM providers to test whether an AI would endorse a brand for a given topic or query. By aggregating repeated trials into a percentage-based relevance score (QRS), the system measures commercial affinity and can uncover specific relevance gaps where competitors are recommended instead.