Document processing is increasingly vital in enterprise applications, especially as businesses face diverse and complex document types. Traditional Optical Character Recognition (OCR) methods often fall short in efficiency due to their reliance on rigid templates and pattern recognition. As the volume of unstructured documents grows—including emails, contracts, and handwritten notes—there's a pressing need for more adaptable solutions. Modern document intelligence systems leverage modular pipelines for better data management. Vendors offer various AI solutions, allowing organizations to combine pre-built and custom models to optimize processes and enhance compliance.
Document processing is critical in enterprise applications. Failure to correctly extract data leads to operational delays and increased manual correction cycles.
Modern document intelligence systems rely on modular pipeline architecture which includes stages for data capture, classification, extraction, enrichment, validation, and consumption.
Cloud vendors and open-source tools offer a variety of document AI services, including Google Document AI, Azure Form Recognizer, AWS Textract, and LayoutLM.
Most real-world document processing pipelines benefit from a hybrid strategy combining pre-trained APIs' speed and simplicity with the precision of custom models.
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