AWS Certified Generative AI Developer - Professional AIP-C01Demo

A company uses an AWS Organizations organization with all features enabled to manage multiple AWS accounts. Employees use Amazon Bedrock in multiple accounts. The company must prevent particular topics and proprietary information from being included in prompts submitted to Amazon Bedrock models. The company must ensure that employees can use only approved Amazon Bedrock models. The company centrally administers IAM roles for employees.

Which combination of solutions will satisfy these requirements?

A company is developing a generative AI (GenAI) application that generates content from a range of internal and external data sources. The company needs to ensure that all generated output is fully traceable. The application must support registering data sources and allow metadata tagging to attribute content to its original source. It must also retain audit logs of data access and usage across the entire pipeline.

Which solution meets these requirements?

A company is developing a generative AI (GenAI) application that uses Amazon Bedrock APIs to process complex customer inquiries. During periods of peak use, the application has intermittent API timeouts that result in issues such as broken response chunks and delayed data delivery. The application has difficulty ensuring prompts stay within token limits when processing complex customer inquiries of different lengths. Users have reported truncated inputs and incomplete responses. The company has also identified foundation model (FM) invocation failures.

The company requires a retry strategy that automatically manages transient service errors and avoids overwhelming Amazon Bedrock during peak usage periods. The strategy must adapt to changing service availability and support response streaming and token-aware request handling.

Which solution meets these requirements?

An enterprise application uses an Amazon Bedrock foundation model (FM) to process and analyze technical documents of 50 to 200 pages. Users experience inconsistent responses and truncated outputs when processing documents that exceed the FM's context-window limits.

Which solution will solve this problem?

A retail company uses Amazon Bedrock to build a customer service AI assistant. Analysis indicates that 70% of customer inquiries are simple product questions that a smaller model can handle effectively. However, 30% of inquiries are complex return-policy questions requiring advanced reasoning. The company wants to implement a cost-effective model-selection framework that automatically routes customer inquiries to appropriate models according to inquiry complexity. The framework must preserve high customer satisfaction and minimize response latency.

Which solution meets these requirements with the LEAST implementation effort?

A company uses AWS Lambda functions to create an AI agent solution. A GenAI developer must configure a Model Context Protocol (MCP) server that accesses user information. The GenAI developer must also configure the AI agent to use the new MCP server. The GenAI developer must ensure that only authorized users can access the MCP server.

Which solution meets these requirements?

A GenAI developer is developing a Retrieval Augmented Generation (RAG)-based customer-support application that uses Amazon Bedrock foundation models (FMs). The application must process 50 GB of historical customer conversations stored as JSON files in an Amazon S3 bucket. It must use the processed data as its retrieval corpus.

The application's data-processing workflow must extract relevant data from customer-support documents, remove customer personally identifiable information (PII), and generate embeddings for vector storage. The workflow must be cost-effective and complete within 4 hours.

Which solution meets these requirements with the LEAST operational overhead?

A company uses Amazon Bedrock to create technical content for customers. The company has recently seen a surge in hallucinated outputs when its model produces summaries of lengthy technical documents. The outputs contain incorrect or invented details. The current solution uses a large foundation model (FM) with a basic one-shot prompt that supplies the complete document in one input.

The company needs a solution that reduces hallucinations and satisfies factual-accuracy objectives. The solution must process more than 1,000 documents per hour and provide summaries within 3 seconds for each document.

Which combination of solutions meets these requirements?

A company upgraded its Amazon Bedrock-powered foundation model (FM) that supports a multilingual customer service assistant. Following the upgrade, the assistant showed inconsistent behavior between languages. It started producing different responses in some languages for identical questions.

The company needs a solution to identify and remediate similar issues in future updates. The evaluation must:

• Complete within 45 minutes for every supported language.
• Process at least 15,000 test conversations concurrently.
• Be fully automated and integrated into the CI/CD pipeline.
• Prevent deployment when quality thresholds are not met.

Which solution meets these requirements?

A large ecommerce company has deployed a foundation model (FM) to create product descriptions. The company’s engineering team uses Amazon CloudWatch to monitor technical metrics such as token usage, latency, and error rates. Its marketing team tracks business metrics, including conversion rates and revenue impact, in separate systems.

The company requires a unified observability solution that correlates technical performance with business outcomes. The solution must automatically alert stakeholders when operational metrics show degradation. It must also deliver comprehensive visibility across both technical and business metrics.

Which solution meets these requirements?

A financial services company is building a Retrieval Augmented Generation (RAG) application to help investment analysts query complex financial relationships spanning multiple investment vehicles, market sectors, and regulatory environments. The dataset includes highly interconnected entities with multi-hop relationships. Analysts must be able to review these relationships holistically to deliver accurate investment guidance. The application must provide comprehensive answers that include indirect relationships among financial entities. The application must return responses in under 3 seconds.

Which solution meets these requirements with the LEAST operational overhead?

A company uses Amazon Bedrock to build an AI-powered application with a foundation model (FM) that supports cross-Region inference and provisioned throughput. The application must provide consistently low latency to users in Europe and North America. It must also comply with data-residency regulations requiring European user data to stay in Europe-based AWS Regions.

During testing, the application has service degradation when Regional traffic spikes reach service quotas. The company requires a solution that preserves application resilience while minimizing operational complexity.

Which solution meets these requirements?

A company is developing a legal-research AI assistant that uses Amazon Bedrock with an Anthropic Claude foundation model (FM). The AI assistant must retrieve highly relevant case-law documents to augment the FM’s responses. It must recognize semantic relationships among legal concepts, specific legal terminology, and citations. The AI assistant must operate quickly and return precise results.

Which solution meets these requirements?

A company is developing a canary deployment strategy for a payment-processing API. The system must support automated, gradual traffic shifting among multiple Amazon Bedrock models based on real-time inference metrics, historical traffic patterns, and service health. The solution must be able to progressively increase traffic to new model versions. It must increase traffic when metrics stay healthy and reduce traffic when performance degrades below acceptable thresholds.

The company needs comprehensive monitoring of inference latency and error rates throughout the deployment phase. The company must also be able to stop deployments and roll back to a previous model version without manual intervention.

Which solution meets these requirements?

A company operates a recommendation system whose applications run on Amazon EC2 instances. The applications make API calls to Amazon Bedrock foundation models (FMs) to analyze customer behavior and produce personalized product recommendations.

The system is having intermittent problems. Some recommendations fail to align with customer preferences. The company requires an observability solution that monitors operational metrics and identifies patterns of operational performance degradation against established baselines. The solution must also produce alerts containing correlation data within 10 minutes when FM behavior departs from expected patterns.

Which solution meets these requirements?

A company uses Amazon Bedrock to build an AI assistant that provides customer support. Analysis indicates that 40% of customer queries use different phrasing or wording to ask the same questions.

The company needs a solution that reduces redundant model calls, ensures semantically equivalent questions receive consistent answers, and provides low latency.

Which solution meets these requirements?

A medical company is developing a generative AI (GenAI) application that uses RAG to deliver evidence-based medical information. The application uses Amazon OpenSearch Service to retrieve vector embeddings. Users report that searches often miss results containing exact medical terms and acronyms, while returning too many semantically similar but irrelevant documents. The company must improve retrieval quality while keeping end-user latency low, even as the document collection scales to millions of documents.

Which solution meets these requirements with the LEAST operational overhead?

A company is developing an API for a generative AI (GenAI) application that uses a foundation model (FM) hosted on a managed model service. The API must stream responses to lower latency, enforce token limits to control compute resource usage, and implement retry logic for model timeouts and partial responses.

Which solution meets these requirements with the LEAST operational overhead?

A company is building a workflow to review customer-facing communications before it sends them. The company uses a predefined message template to generate the communications and stores the communications in an Amazon S3 bucket. The workflow must extract a specific portion of the template and send it to an Amazon Bedrock model. The workflow must save model responses back to the original S3 bucket.

Which solution meets these requirements?

An e-commerce company is building an internal platform for developing generative AI applications with Amazon Bedrock foundation models (FMs). Developers must choose models based on evaluations aligned with e-commerce use cases. The platform must show accuracy metrics for text generation and summarization in dashboards. The company has custom e-commerce datasets to use as standardized evaluation inputs.

Which combination of steps meets these requirements with the LEAST operational overhead?

A financial services company must build a document-analysis system using Amazon Bedrock to process quarterly reports. The system must analyze financial data, perform sentiment analysis, and validate compliance across batches of reports. Each batch contains 5 reports. Each report requires multiple foundation model (FM) calls. The solution must complete the analysis within 10 seconds for every batch. The current sequential processing takes 45 seconds for each batch.

Which solution will satisfy these requirements?

A company is developing an AI advisory application with Amazon Bedrock that will provide recommendations to customers. The company requires the application to explain its reasoning and cite specific data sources. It must retrieve information from company data sources and present step-by-step reasoning for its recommendations. It must also connect data claims to source documents and keep response latency below 3 seconds.

Which solution meets these requirements with the LEAST operational overhead?

A specialty coffee company has a mobile app that uses Amazon Bedrock and a three-stage prompt chain to generate personalized coffee roast profiles. The prompt chain converts user inputs into structured metadata, retrieves relevant coffee-roast logs, and produces a personalized roast recommendation for each customer.

Users across multiple AWS Regions report inconsistent roast recommendations for identical inputs, slow inference in the retrieval step, and unsafe recommendations, such as brewing at excessively high temperatures. The company must improve output stability for repeated inputs, application performance, and the safety of the application's outputs. The updated solution must ensure 99.5% output consistency for identical inputs and inference latency of less than 1 second. The solution must also block unsafe or hallucinated recommendations by using validated safety controls.

Which solution will meet these requirements?

A media company is releasing a platform that enables thousands of users each hour to upload images and text content. The platform uses Amazon Bedrock to process uploaded content and generate creative compositions.

The company requires a solution that ensures the platform neither processes nor produces inappropriate content. The platform must not reveal personally identifiable information (PII) in the compositions. The solution must integrate with the company’s existing Amazon S3 storage workflow.

Which solution meets these requirements with the LEAST infrastructure-management overhead?