How to Build an AI Application for Customer Claims Using Amazon Bedrock?

AIF-C01 By islever Editorial Last updated

Short answer

B Use Agents for Amazon Bedrock with Amazon Bedrock knowledge bases to build the application.

Question

A company wants to develop an AI application to help its employees check open customer claims, identify details for a specific claim, and access documents for a claim. Which solution meets these requirements?
  1. Use Agents for Amazon Bedrock with Amazon Fraud Detector to build the application.
  2. Use Agents for Amazon Bedrock with Amazon Bedrock knowledge bases to build the application. Correct Answer
  3. Use Amazon Personalize with Amazon Bedrock knowledge bases to build the application.
  4. Use Amazon SageMaker to build the application by training a new ML model.

Key Takeaways

The question evaluates understanding of how Agents for Amazon Bedrock orchestrate actions and how knowledge bases provide access to proprietary data sources like claim documents.

This question tests the knowledge of combining Agents for Amazon Bedrock with Amazon Bedrock knowledge bases to build an AI application capable of retrieving claim details and documents. The community unanimously agrees that this combination is the optimal solution for enterprise data retrieval and interaction.

Common mistake: Candidates might choose Amazon SageMaker (Option D) thinking a custom model is needed, or Amazon Fraud Detector (Option A) confusing the use case with fraud detection rather than information retrieval.

Expert Analysis

Understanding the Requirement

The scenario describes an AI application that needs to:

  1. Check open customer claims (querying a system)
  2. Identify details for a specific claim (retrieving structured data)
  3. Access documents for a claim (retrieving unstructured data/files)

This is a classic Retrieval-Augmented Generation (RAG) and agentic workflow use case, where the AI needs to interact with enterprise data sources.

Why Option B is Correct

Agents for Amazon Bedrock combined with Amazon Bedrock knowledge bases is the ideal solution because:

  • Agents for Amazon Bedrock can orchestrate multi-step tasks, call APIs to check claim statuses, and interact with enterprise systems
  • Amazon Bedrock knowledge bases provide managed RAG capabilities, allowing the agent to retrieve relevant documents and claim details from structured and unstructured data sources (S3, databases, etc.)
  • Together, they enable natural language interaction where employees can ask questions and get accurate, sourced answers from company data

Why Other Options Are Incorrect

  • Option A (Amazon Fraud Detector): This service is specifically designed for detecting fraudulent activities, not for retrieving claim information or documents. It's a mismatch for the stated requirements.
  • Option C (Amazon Personalize): This is a machine learning service for building recommendation systems (e.g., product recommendations, personalized content). It has no relevance to claim management or document retrieval.
  • Option D (Amazon SageMaker): While SageMaker can build custom ML models, it requires significant effort to train, deploy, and maintain. For a document retrieval and query application, using pre-built Bedrock capabilities is far more efficient and appropriate than training a new model from scratch.

Community Consensus

All community members (100% vote for B) correctly identified that Agents + Knowledge Bases is the standard AWS pattern for building enterprise AI applications that need to access proprietary data. As noted by multiple commenters, this combination allows the agent to "connect to and interact with various data sources" effectively.

Official Reference

These links open the official vendor documentation in a new tab.

Exam Strategy

When you see requirements involving 'accessing documents,' 'retrieving details,' or 'querying enterprise data' in an AI context, immediately think of Amazon Bedrock knowledge bases for RAG and Agents for Amazon Bedrock for orchestration. Eliminate options that mention specialized services (Fraud Detector, Personalize) unless the use case explicitly matches their purpose.

Community Votes

B
100%

100% of anonymous learners picked answer B. Votes are pick records left by other test-takers — they are not the verified answer.

Discussion 5 contributions

Compiled from public community threads and reader submissions, lightly edited for clarity. Handles and vote tallies are shown as recorded, and comments reflect the views of individual contributors.

From public community threads 5

  1. ap6491 👍 1 Answered B
    Agents for Amazon Bedrock enable the creation of AI-driven applications that integrate with enterprise systems and use natural language processing (NLP) to answer user queries. Amazon Bedrock knowledge bases allow the agent to access structured and unstructured data, such as claim details and associated documents, enabling employees to search and retrieve specific claim-related information efficiently. This combination supports the application’s requirement to check open claims, identify specific claim details, and access claim documents.
  2. aws_Tamilan 👍 1 Answered B
    B. Use Agents for Amazon Bedrock with Amazon Bedrock knowledge bases to build the application. Explanation: Amazon Bedrock is a fully managed service that allows you to build and deploy generative AI applications. Agents for Amazon Bedrock provides AI-powered agents to interact with users and help them get information, making it ideal for helping employees check open customer claims, identify claim details, and access documents.
  3. Moon 👍 1 Answered B
    B. Use Agents for Amazon Bedrock with Amazon Bedrock knowledge bases to build the application: This is the correct answer. Agents for Bedrock can connect to and interact with various data sources, including knowledge bases. Using a Bedrock knowledge base (which could be populated with claim data and documents) allows the agent to retrieve the necessary information to fulfill user requests related to claims.
  4. may2021_r 👍 1 Answered B
    The correct answer is B. Using Agents for Amazon Bedrock with Amazon Bedrock knowledge bases allows employees to check open customer claims, identify details, and access related documents effectively.
  5. Jessiii 👍 1 Answered B
    Amazon Bedrock agents and knowledge bases are designed to help build AI-powered applications that can understand and access specific claim details and documents.

Reader comments & corrections

No reader corrections yet — spotted an error or have a note? Share it below.

Log in to comment, report an error, or add a note about this question.

How to use a custom trained model in Amazon Bedrock?

S-grade

How to Increase Image Specificity in Amazon Bedrock Stable Diffusion?

S-grade

How to Quickly Deploy and Consume Foundation Models in a VPC on AWS?

S-grade

Which AWS Service Sends Email Notifications When ISV Compliance Reports Are Available?

S-grade

Practice All AIF-C01 Questions

Access 100 questions with complete answers and detailed explanations.

View Full AIF-C01 Practice Test →

← Back to AIF-C01 Study Guide