Your team is building a retrieval-augmented generation solution in Azure AI Foundry that answers questions over a large corpus of technical support articles. Early testing shows the agent retrieves semantically similar passages but frequently misses documents where users search using exact product model numbers and error codes. You must improve retrieval accuracy for both conceptual queries and exact keyword matches without maintaining two separate query pipelines. Which retrieval configuration should you implement in your Azure AI Search index?