Document data capture is crucial for businesses to efficiently process both structured and unstructured documents, converting them into electronic data for machine use. Traditional manual data capture is prone to errors and time-consuming, but modern technologies like AI and Optical Character Recognition (OCR) offer automated solutions that enhance accuracy and efficiency. Various technologies are used based on business needs, including Intelligent Character Recognition (ICR) for handwritten text, Intelligent Document Recognition (IDR) for complex data, Optical Mark Recognition (OMR) for surveys, and barcodes and QR codes for quick data retrieval. The document data capture process involves importing, processing, validating, classifying, and extracting document data, which reduces costs, saves time, and increases accuracy. Automated solutions like Nanonets further optimize this process by leveraging AI to reliably capture and manage data from diverse documents, ensuring security and compliance while enhancing business operations.