Better Search Took This AI Agent From 36% to 98% Accuracy - Aamir Shakir, Mixedbread
Agents are smart enough. Most of the time, the real problem is getting them to the right data. Aamir Shakir of Mixedbread explains why the usual stack of OCR, chunking, embeddings and a vector database loses information and leaves agents reading every document. He shows multimodal, late-interaction retrieval on Intel earnings reports, and shares a customer whose answer accuracy went from 36% to 98% after switching their search. 0:00 Intro to Mixedbread 1:30 The equity analyst problem 3:30 The key bottlenecks 4:00 The "Frankenstein stack": OCR, chunking and vectors 6:02 Why "just add a vector database" falls short 8:26 The bottleneck is access to your data 9:04 How retrieval has evolved 11:08 Demo: searching Intel earnings reports 14:57 Customer result: 36% to 98% accuracy Aamir Shakir, Mixedbread Join us in SF for the second annual AIE CODE summit: https://aie.codes our last flagship summit of 2026. Applications live now!




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