A functional automated document processing pipeline typically needs to know what type of document it’s dealing with before it can do anything useful with it. The extraction logic that determines when it’s dealing with an invoice, for example, is different from the extraction logic for a tax form, and the routing rules for a contract are clearly different from those for an ID document. Classification is what makes downstream automation possible when there are multiple unique input types.
Building reliable classification logic, however, is no simple task. It’s easy to create something brittle, and much harder to create something dynamic and flexible that works reliably in the majority of cases. In this article, we’ll look at why classification breaks down at scale, and we’ll examine what it actually takes to build and maintain a reliable solution in C#. Towards the end, we’ll walk through a dedicated API that handles classification across a wide range of document formats using AI without requiring a specially trained model for each document type.
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