• Enhance data extraction and perform several pre/post processing actions • Cognitive processes that can process unstructured and semi structured data to power intelligent automation of end to end processes. • Machine Learning / Natural Learning Process, Crowdsourcing AI to get truly intelligent automation. • Own AI engine, such as a natural language processing (NLP) engine, to automatically compare extracted data against an existing database for verification • Rapidly build custom AI capabilities that are available for any business user to deploy, Focused on artificial intelligence and cognitive automation. • Rapid build on Documents that are preprocessed (crop, noise reduction, etc.), indexed, and classified by the intelligent document classifier. These classified documents are then sent for data extraction by OCR based on type: fixed format (such as ACORD or UB 04) or variable format (such as invoices, purchase orders, etc • Full capabilities of automatic layout analysis, field recognition on paper, and compatibility with multiple languages and document types • AI driven extraction capabilities for more than 30 common business document types, including invoices, purchase orders, insurance claims, mortgage forms, bank statements, and explanation of benefits. • Intelligent automation the integration of AI, machine learning, and RPA . Next era of automation and, when combined with artificial intelligence (AI) • Analyses were needed, run the data through a custom AI analytical model written in Python