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AWS Certified Generative AI Developer - Professional
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A healthcare company creates a custom foundation model (FM) that uses a proprietary architecture to summarize and answer questions about sensitive patient records and conversations. To comply with regulations, the company must ensure confidentiality by implementing extensive monitoring and controls. The company must verify the accuracy of the FM by checking prompts and responses for hallucinations. Which solution will meet these requirements?
A financial services company provides an Amazon Bedrock-powered AI assistant that provides investment guidance to customers. Recent audits found racially and genderbiased responses. Auditors flagged several cases as potential regulatory compliance risks. The company must implement a 30-day remediation plan to eliminate biased outputs. The plan must preserve model accuracy and keep latency within acceptable customerexperience thresholds. A GenAI developer must design a long-term solution that balances regulatory risks, operational scalability, and model-agnostic enforcement. The solution must apply enforceable at-inference-time controls so bias mitigation measures cannot be bypassed. The solution must provide logging for each inference for audit and regulatory reviews. The solution must support ongoing automated bias monitoring. The solution must not require any model re-training within 30 days. The solution must add minimal inference latency. Which solution will meet these requirements?
A financial services company is using Amazon Bedrock to deploy a GenAI application across multiple business units. The company must ensure that all prompts that are used with the application's FMs follow regulatory compliance standards and maintain consistent formatting. The company must implement a solution that provides version control for prompt templates, requires approval workflows for new prompts, and maintains detailed audit trails of all prompt usage and modifications. Which combination of solutions will meet these requirements? (Select TWO.)
A GenAI developer is using Amazon Bedrock AgentCore to build an agentic AI application. The application orchestrates multiple foundation models (FMs) across development and production environments. The application experiences intermittent failures during tool invocation phases. Each incident requires an average of 3 hours to diagnose because of complex error patterns in the FM chains. The GenAI developer needs a solution that can identify AI-specific error patterns in tool invocation chains in less time than the existing manual process. The solution must support collaboration between development and security teams. The solution must provide capabilities to protect sensitive customer data. Which solution will meet these requirements?
A global research company is building a RAG-enabled AI system that uses Amazon Bedrock Knowledge Bases. The company stores documents in Amazon S3 and indexes the documents into an Amazon OpenSearch Serverless vector collection. When the company evaluates the system, the company identifies three issues. Queries return outdated documents when users request only recent research. Medical research queries return both medical research documents and engineering domain documents. Users can retrieve documents that were authored by researchers who the users should not have access to based on company policies. The company wants to improve the system so that retrieval becomes more precise and contextually appropriate. Which solution will meet these requirements?
A healthcare company is developing an Amazon Bedrock-based AI clinical assistant. The company needs a solution to track model inputs and outputs so the company can perform offline quality evaluation and regression analysis. The solution must provide centralized, immutable audit records of all model inference and decision events. The company needs a solution that requires minimal runtime overhead so interactive latency remains stable during evaluation and auditing. Which solution will meet these requirements?
A company is building an AI-powered customer support application that uses Amazon Bedrock FMs. The application must provide users with recommendations based on an internal Amazon Bedrock knowledge base. Users will query documents that the company stores in Amazon S3 and structured data that is in Amazon RDS. The application must provide citations for the sources it uses to generate recommendations. The application must also provide secure access to sensitive data. Which solution will meet these requirements?
A healthcare company is building a generative AI (GenAI) application to answer patient questions based on patient medical records and published treatment guidelines. To comply with healthcare regulations, the application must provide transparent citations for all information sources. The application must also maintain an audit trail for all data access and ensure that responses reference only authorized medical information. Which solution will meet these requirements with the LEAST operational overhead?
A company is using Amazon Bedrock to build an AI assistant to help internal teams analyze unstructured customer feedback data. The company stores the customer feedback in an Amazon S3 bucket. The S3 bucket contains more than 25 TB of historical data from mobile app reviews, chat conversations, and call center transcripts. The company expects the data source to grow by 3 GB every day. The data entries often contain multiple unrelated topics within the same input. The company needs a solution that reliably delivers accurate answers to questions based on the data source. The solution must not export any personally identifiable information (PII) to the Amazon Bedrock model during processing or response generation. Which solution will meet these requirements with the LEAST operational overhead?
A healthcare company is developing a generative AI (GenAI) application that recommends patient treatment plans to physicians. The company wants to use Amazon Bedrock to build the application. The application must document model limitations, prevent unauthorized clinical recommendations, and maintain detailed audit trails of all AI-generated outputs. The company must store outputs in compliance with healthcare regulations. The solution must prevent output tampering. Which solution will meet these requirements?