A company uses a pre-trained foundation model on Amazon Bedrock but wants to provide it with more company-specific context. Which option is the most cost-effective way to add that context?

Amazon Bedrock Knowledge Bases are the most cost-effective way to add company-specific context to a pre-trained foundation model. Knowledge Bases allow you to connect FMs to your data sources for Retrieval Augmented Generation (RAG), providing relevant information without retraining the model. This is significantly cheaper than fine-tuning or deploying a custom model. Choosing a different FM might not provide the specific context needed. Amazon Bedrock Agents orchestrate complex tasks but don't primarily focus on injecting context into the FM's knowledge base. Deploying a custom model is expensive and time-consuming, requiring extensive data and training.