Data capture is the process of converting information from structured or unstructured documents into a machine-readable digital format, significantly enhanced by AI technologies, allowing for automatic extraction, classification, and validation of data. Traditional methods like manual data entry are giving way to automated techniques such as Optical Character Recognition (OCR), Intelligent Character Recognition (ICR), and Intelligent Document Recognition (IDR), which streamline data processing in various sectors like healthcare, finance, and customer service. Automated data capture reduces human errors, operational costs, and enhances security and efficiency by providing centralized, 24/7 access to data, thus improving employee satisfaction and customer service. Technologies such as barcodes, QR codes, digital forms, web scraping, and smart cards further support diverse data capture needs, while platforms like Nanonets offer no-code solutions to automate data workflows, enhancing business decision-making and productivity.