A creamery has a private 12-year pasteurizer-fault log and needs to train and host its own predictor. Prompting a public foundation model is not enough. Which AWS service matches this job?
Select an answer to reveal the explanation.
Short Explanation
Think of a private 12-year log that needs its own trained predictor. That is SageMaker AI. Prompting Bedrock is not enough, Quick does not train, and an IDE is not the production host.
Full Explanation
Amazon SageMaker AI is the practitioner match for training and hosting a custom model on a private log. Amazon Bedrock consumes foundation models and does not replace that custom lifecycle. Amazon Quick visualizes data; it does not train the predictor. Kiro is a developer environment, not the production host for that model.