The OCR technology has become a vital component for businesses looking to automate document processing and streamline data extraction. Optical Character Recognition (OCR) involves scanning documents with a PDF scanner and converting the scanned image into machine-readable text, allowing organizations to process a wide variety of documents without manual data entry. OCR APIs act as an extension of this functionality by providing developers with a pre-built "black box" that can be accessed programmatically, eliminating the need to build or develop OCR from scratch. The OCR API landscape has witnessed significant transformations over the past five years, with newer solutions such as CRF and LSTM offering improved accuracy, multi-language document processing support, and the ability to process complex document structures. Large language models like OpenAI's GPT-4 and Anthropic's Claude have introduced OCR capabilities, allowing for a more natural interaction with documents. AI-based Intelligent Document Processing (IDP) platforms have carved out a niche by offering highly specialized, industry-specific OCR and document processing workflow automation capabilities. To identify the best OCR APIs available today, categories were established, including cloud service providers, large language models, and AI-based IDP software. Cloud service providers offer open APIs that are scalable and provide enterprise-grade security, while LLMs started off as AI algorithms that could process information and generate human-like responses have expanded their feature suite to include OCR capabilities. AI-based IDPs were found to be the most important category of the three, offering highly specialized OCR and document processing workflow automation capabilities. The primary criteria for evaluating any OCR API is accuracy, followed by language support, advanced features, and pricing. A sample set of documents was chosen to test out various OCR APIs, including a creased invoice, Hindi-language invoice, badly scanned receipt, passport, bank statement, and handwritten legal document. The top OCR APIs from each category were evaluated based on their performance criteria, including accuracy, language support, advanced features, and pricing. Google Vision API offered accurate results for all 6 documents tested, but not as key-value pairs. AWS Textract Forms API provided accurate results for 5 documents as key-value pairs, but had limited support for complex and multi-language documents. GPT-4o offered accurate results for all 6 documents, but was more expensive than dedicated OCR solutions. Claude offered decent accuracy for 4 documents, but was more expensive than modern-day IDP software with specific OCR capabilities. Nanonets offered pre-trained models for common documents with high accuracy, supporting over 110+ languages, including Asian and European languages. Veryfi offered accurate results for 4 documents, but had limited support for non-financial documents and a less flexible pricing model compared to Nanonets. Depending on the size of your business, the types of documents you process, and your budget, one of these tools will likely be the best fit for your OCR API needs.