AIF-C01 · Question #287
A company wants to create a chatbot to answer employee questions about company policies. Company policies are updated frequently. The chatbot must reflect the changes in near real time. The company…
The correct answer is C. Create a Retrieval Augmented Generation (RAG) workflow by using Amazon Bedrock Knowledge. A RAG workflow with Amazon Bedrock Knowledge Bases allows the chatbot to access the most recent company policy documents dynamically, ensuring responses reflect policy updates in near real time without the need to retrain or fine-tune the LLM each time content changes.
Question
A company wants to create a chatbot to answer employee questions about company policies. Company policies are updated frequently. The chatbot must reflect the changes in near real time. The company wants to choose a large language model (LLM). Which solution meets these requirements?
Options
- AFine-tune an LLM on the company policy text by using Amazon SageMaker.
- BSelect a foundation model (FM) from Amazon Bedrock to build an application.
- CCreate a Retrieval Augmented Generation (RAG) workflow by using Amazon Bedrock Knowledge
- DUse Amazon Q Business to build a custom Q App.
How the community answered
(36 responses)- A11% (4)
- B22% (8)
- C61% (22)
- D6% (2)
Explanation
A RAG workflow with Amazon Bedrock Knowledge Bases allows the chatbot to access the most recent company policy documents dynamically, ensuring responses reflect policy updates in near real time without the need to retrain or fine-tune the LLM each time content changes.
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