The text discusses key-value pair (KVP) extraction, a technique used to extract valuable information from unstructured data or unfamiliar formats. KVPs are pairs of linked data elements: a unique identifier (key) and its associated data (value). The technique is widely applicable in various domains, including personal use cases such as ID scanning and data conversion, invoice data extraction for budgeting, email organization and prioritization, business use cases like automation of document scanning, survey collection and statistical analysis, supply chain management, healthcare record management, legal document analysis, and customer service optimization. Traditional approaches to KVP extraction rely on Optical Character Recognition (OCR) processes, which have limitations such as template dependence, handwriting detection issues, lack of context, and inflexibility. Deep learning techniques, particularly convolutional neural networks (CNNs), have revolutionized the field by enabling machines to understand document structures and extract key-value pairs with remarkable accuracy. The Tesseract OCR engine, a long short-term memory (LSTM) model, is an example of deep learning approach for KVP extraction. Other approaches like Deep Reader are also explored which uses neural networks to recognize shapes and formats beyond just words and symbols of a scanned document. The text also provides code implementation for KVP extraction using Python libraries such as openCV and PyTesseract. Best practices and optimization techniques for key-value extraction include cleaning images, standardizing formats, creating custom dictionaries, using regular expressions, validating extracted data, handling exceptions, using parallel processing, implementing caching, implementing feedback loops, regularly updating models, encrypting sensitive data, and implementing access controls. The text concludes by discussing key-value databases and their differences with relational databases, and platforms like Nanonets that offer a powerful OCR API for key value extraction.