Retrieval Quality evaluates how relevant, complete, and useful retrieved information is for answering user requests accurately. It considers both relevance and contextual usefulness.
Voice AI providers continuously optimize Retrieval Quality through better embeddings, query rewriting, metadata filtering, and re-ranking to improve customer responses and reduce hallucinations.