Zonal OCR, also known as Template OCR or Zone OCR, is a specialized form of Optical Character Recognition technology that focuses on extracting specific parts of a document rather than processing the entire text, offering improved accuracy and control in data extraction and document formatting. By defining specific zones within a document, Zonal OCR captures only the relevant data fields, making it highly effective for tasks like invoice digitization, purchase order processing, and ID card recognition, while reducing manual data entry and enhancing workflow automation. However, challenges such as document quality, handling complex formats, and scalability issues can affect its performance. Advanced AI-based OCR solutions, like Nanonets, overcome many of these limitations by leveraging machine learning to handle semi-structured and unseen document types, offering continuous learning, customization, and integration capabilities without the need for predefined templates, thus streamlining data capture processes across various applications.