A company deploys a foundation model (FM).

The verified answer is A. Amazon Bedrock Guardrails. The requirement is to prevent a deployed foundation model from returning answers about a specific unwanted topic: politics. AWS documentation states that Amazon Bedrock Guardrails provides configurable safeguards to help you build safe generative AI applications. It also explains that guardrails provide safety and privacy controls across foundation models and help detect and filter undesirable content in user inputs and model responses. Most importantly for this question, AWS specifically identifies denied topics as a guardrail capability. With denied topics, you can define a set of topics that are undesirable in the context of your application, and the filter helps block them if they are detected in user queries or model responses. That exactly matches the scenario because the company wants political questions blocked before answers are sent to users.

Amazon Bedrock Agents is incorrect because agents are used to build applications that can reason, orchestrate tasks, call APIs, and connect to knowledge sources or action groups. Agents do not primarily exist to block topic categories in model input or output. Amazon SageMaker Clarify is incorrect because AWS describes SageMaker Clarify as a service for fairness, model explainability, feature attribution, and bias detection. It is useful for understanding model behavior and detecting bias, but it is not the correct control for filtering political responses from a generative AI application.

Amazon SageMaker Model Monitor is also incorrect because it monitors deployed model quality, data quality, bias drift, and feature attribution drift. Monitoring can identify problems after deployment, but it does not directly enforce real-time content filtering for foundation model responses. The question asks for a solution that ensures political answers are not sent to users. AWS Bedrock Guardrails is purpose-built for that control by applying safeguards to FM inputs and outputs.