Automated Evaluation

An evaluation approach that uses another trained model to assess the quality, correctness, safety, or other properties of an AI system's outputs.

An evaluation method that uses a large language model to assess the quality, correctness, or other attributes of AI-generated outputs.

An evaluation performed outside production using fixed datasets, test cases, or recorded interactions to assess an AI system before deployment.

An evaluation approach that continuously measures AI system performance throughout development and production to detect regressions and ensure quality.

An evaluation method in which human reviewers assess the quality of AI system outputs against defined criteria such as correctness, relevance, helpfulness, safety, or fluency, providing judgments that complement or validate automated evaluation metrics.