AWS Certified Generative AI – Professional (AIP-C01) — Question 15

An ecommerce company is developing a generative AI (GenAI) solution that uses Amazon Bedrock with Anthropic Claude to recommend products to customers. Customers report that some of the recommended products are not available for sale on the website or are not relevant to the customer. Customers also report that the solutions takes a long time to generate some recommendations.
The company investigates the issues and finds that most interactions between customers and the product recommendation solution are unique. The company confirms that the solutions recommends products that are not in the company's product catalog. The company must resolve these issues.
Which solution will meet this requirement?

Answer options

• A. Increase grounding within Amazon Bedrock Guardrails. Enable Automated Reasoning checks. Set up provisioned throughput.
• B. Use prompt engineering to restrict the model responses to relevant products. Use streaming techniques such as the InvokeModelWithResponseStream action to reduce perceived latency for the customers.
• C. Create an Amazon Bedrock knowledge base. Implement Retrieval Augmented Generation (RAG). Set the PerformanceConfigLatency parameter to optimized.
• D. Store product catalog data in Amazon OpenSearch Service. Validate the model's product recommendations against the product catalog. Use Amazon DynamoDB to implement response caching.

Correct answer: C

Explanation

The correct answer is C because creating a knowledge base and implementing Retrieval Augmented Generation (RAG) will ensure that the recommendations are based on available products and improve relevance. Optimizing the PerformanceConfigLatency parameter will also help reduce response time. The other options either do not address the core issue of irrelevant recommendations or do not effectively enhance the response time.