Abstract-A simple and efficient pipeline for word spotting in handwritten documents is proposed. The method allows for extremely rapid querying, while still maintaining high accuracy. The dataset images that are to be queried are preprocessed by a simple binarization operation, followed by the extraction of multiple overlapping candidate targets. Each binary target, as well as the binarized query, is resized to fit a fixed-size rectangle and represented by conventional image descriptors. Then, a cosine similarity operator-followed by maximum pooling over random groups-is used to represent each target or query as a concise 250D vector. Retrieval is performed in a fraction of a second by nearest-neighbor search within that space, followed by a simple suppression of extra overlapping candidates.