Latest

Pre-built evaluation metrics cover common quality dimensions like accuracy, relevance, and coherence. However, production AI applications require validation against domain-specific business rules, compliance requirements, and proprietary quality standards that generic evaluators cannot assess. Custom evaluators enable teams to enforce these specialized quality checks across AI agent workflows, ensuring

AI agents have evolved beyond simple question-answer systems into complex, multi-step entities that plan, reason, retrieve information, and execute tools across dynamic conversations. This evolution introduces significant evaluation challenges. Unlike traditional machine learning models with static inputs and outputs, AI agents operate in conversational contexts where performance depends