Mixedbread’s Aamir Shakir describes how OCR, chunking and single-vector embeddings can lose details from tables and other complex documents. He argues that retrieval qualityRetrieval is the process of selecting relevant stored information and returning it to an AI system for the current task. becomes a bottleneck as an agent searches a large knowledge base.
Shakir explains late interactionLate interaction is a retrieval approach that encodes a query and document separately, then compares their detailed representations to score relevance., where multiple contextualized embeddingsAn embedding represents information as a list of numbers that an AI system can compare or process. represent fine-grained document and query information, and demonstrates searching visual financial reports. He reports a customer case in which answer accuracy rose from 36% to 98% after changing retrieval; this is a company-reported result, not an independent comparison.
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