Amazon Q Business Underlying LLM

Hi,

To implement your use case, you should leverage Retrieval-Augmented Generation (RAG). RAG allows you to fetch up-to-date information by integrating with third-party sources. This will help ensure you have the latest and most relevant data for your application or task. Further read, Amazon Q Supported connectors.

Utilising RAG can also help ensure your solution remains future-proof. By integrating with fresh data sources, your application will not be solely dependent on the training data of the underlying model. This means your solution is more likely to continue providing accurate, up-to-date outputs even as time passes and information evolves.

Thanks, Rama

Amazon Q for Business will pick up different LLM's based on the use case, you will not be knowing which LLM is getting used. As mentioned above ,implementing RAG architecture is the right approach.