The article explores how Computer Vision and multimodal AI are transforming enterprise document analysis by extracting meaningful insights from visually rich and complex documents such as infographics, posters, screenshots, and product labels. Unlike traditional OCR, which struggles with inconsistent layouts and scene text, Computer Vision combines image recognition, OCR, graph-based contextual analysis, and NLP to interpret relationships between visual and textual elements. This enables organizations in advertising, marketing, research, retail, healthcare, and manufacturing to automate insight generation at scale with greater speed and accuracy. The paper also discusses challenges such as limited labeled training data, high computational costs, and the need for advanced learning technique

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