A company wants to fine-tune a foundation model (FM) for a specific use case.

Comprehensive and Detailed Explanation From Exact AWS AI documents:

Amazon Bedrock supports importing custom foundation models that have been trained or fine-tuned outside of Bedrock, including models customized using Amazon SageMaker AI.

Amazon SageMaker AI provides:

Full control over model training and fine-tuning

Ability to train models using approved internal datasets

Advanced customization beyond prompt-based techniques

After customization in SageMaker, the trained model can be imported into Amazon Bedrock for managed, scalable inference and internal deployment.

Why the other options are incorrect:

A (Guardrails) enforce safety, compliance, and output controls; they do not create or fine-tune models.

B (Amazon Personalize) is a recommendation service, not a foundation model customization tool.

C (Agents) orchestrate tasks and tool usage but do not modify or fine-tune model weights.

AWS AI document references:

Amazon Bedrock Documentation — section on Custom model import

Amazon SageMaker AI Overview — section on model training and fine-tuning

Foundation Models on AWS — customization approaches