A media company plans to deploy a custom ML model in production to recommend personalized content based on viewer behavior and demographics, and it needs to detect model quality drift over time. Which AWS service fulfills these requirements?

Amazon SageMaker Model Monitor is the correct choice because it continuously monitors the quality of ML models in production. It detects data drift, model drift, and other quality issues, which is crucial for maintaining the effectiveness of a personalized content recommendation system. Amazon Rekognition is incorrect because it is a service for image and video analysis, not for monitoring custom ML models. Amazon Comprehend is incorrect as it's a natural language processing (NLP) service. Amazon SageMaker Clarify is used for detecting bias and explaining predictions in ML models, which is a different function than continuous quality monitoring for drift.