Deep Split: Utilizing Agent Harnesses for Accuracy at Scale

Companies often face the challenge of manually sorting through complex documents to categorize and extract relevant data, a task that is both costly and time-consuming. Split, a tool designed to automate this process, identifies page ranges belonging to different categories using natural-language descriptions and returns the corresponding page numbers. Recently enhanced with an agent harness architecture, Split now efficiently handles longer documents and supports workflows involving numerous categories, providing contextual evidence for page assignments to improve trust and debugging. This improved categorization ensures that downstream data extraction is more accurate and efficient, reducing the risk of processing irrelevant or incorrectly routed pages. A major financial firm has successfully used Split to organize vast data sets and unlock new product features. Split is accessible via an API and can be tried through Studio, with pricing set at 4 credits per page, and demos available upon request.

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