A medical firm is fine-tuning a foundation model for diagnostic use and must provide transparency and explainability to satisfy regulations. Which solution helps provide explainability and simple model metrics?

Amazon SageMaker Clarify provides tools to detect bias in machine learning models and to help explain their predictions. This directly addresses the need for transparency and explainability, offering metrics, reports, and example explanations crucial for regulatory compliance in diagnostic applications. Amazon Inspector is for security and compliance assessment of applications and infrastructure, not ML model explainability. Amazon Macie is a data security and privacy service that discovers and protects sensitive data, not for model explainability. Amazon Rekognition is a computer vision service for image and video analysis; while it can use custom labels, it does not inherently provide model explainability for fine-tuned foundation models.