The 3 Things Clay Measures on Every AI Agent

This post details the evaluation framework Clay uses for AI agents, focusing on three key metrics: quality, throughput, and cost. It explains how factual evaluations, deterministic matching, and LLM-as-a-judge scoring are combined to measure agent accuracy and efficiency. This contributes to the understanding of how to quantitatively assess and improve AI agent performance, building upon the existing capability of agentic PII detection by providing a method for its evaluation.