A company is using the Amazon Titan foundation model via Amazon Bedrock and needs to augment the model with relevant content from the company's private data sources. What should they do?

Creating an Amazon Bedrock knowledge base is the correct approach because it allows you to connect foundation models to your company's private data sources for Retrieval Augmented Generation (RAG). This enables the Titan model to retrieve and incorporate relevant, up-to-date information from your internal documents, databases, or other data stores when generating responses, ensuring accuracy and relevance to your specific business context. Using a different foundation model would not address the need to integrate private data; it just changes the base model. Choosing a lower temperature value controls the randomness of the model's output but doesn't connect it to external data. Enabling model invocation logging records model usage but doesn't augment its knowledge.