Common intelligent document processing integrations include customer service platforms, data enrichment tools, and RPA solutions. Validated data is sent to downstream applications for use. Human input is used to deal with outliers, preprocessing, classification, extraction quality improvement, and additional ML model training. During this step, humans train the machine learning model to identify fields for extraction.Įxtracted data is then validated against internal/external data. Machine learning extracts data from various content types and supports the handling of diverse formats. At this stage, humans are typically involved in document category creation and definition. This can be a manual or an automatic process, with advanced solutions offering suggestions for categories based on existing taxonomies. Some solutions also provide tools for data labeling and annotation, often done by a human-in-the-loop (HITL).ĭocuments are then classified into different categories. This preparation includes merging/splitting documents, and corrections to low quality renders. IDP generally consists of the following five steps.ĭata is captured from several content types and prepared for processing. IDP solutions use machine learning to extract data from documents to support automation efforts. How Does Intelligent Document Processing Work? OCR is a type of software that converts images of text into machine-readable forms. In deep learning, models are trained by using a large set of labeled data and neural network architectures that contain many layers, achieving very high levels of accuracy Machine Learning is a branch of artificial intelligence based on the idea that systems can learn from data and uses computer algorithms to identify patterns and make decisions with minimal human interventionĭeep Learning is a machine learning technique that imitates the way humans gain certain types of knowledge-it learns by example. Intelligent document processing relies on multiple different technologies to operate:Ĭomputer Vision is a technology which is able to derive meaningful information and understanding from videos and digital images, and take actions based on that information IDP solutions understand a wide variety of document formats and the content it contains extracting, validating, and integrating quality data into appropriate business processes and downstream systems.Īdditionally, IDP overcomes the limitations of legacy document capture tools like RPA and OCR and streamlines document processing using human-in-the-loop (HITL) machine learning to handle exceptions and to train and improve its capabilities over time. It uses a combination of technologies, such as optical character recognition (OCR), natural language processing (NLP), computer vision, machine learning (ML) and artificial intelligence (AI), to scan, classify, identify, and extract data. Intelligent document processing helps transform structured (forms), semistructured (checks, paystubs, invoices, etc…) and unstructured data (deeds, medical records, emails, contracts, etc…) from a variety of document formats into digitized and actionable information. It’s in these times that public and private organizations look to increase efficiencies and cut costs by targeting inefficient, manual processes. Times of economic uncertainty create even more demand for document processing technology. IDP software enables organizations of all sizes to remove costly and inefficient manual processes, improve data accuracy, and use their existing employees more effectively.Īccording to Gartner, the IDP market is growing more than 100% year over year, and is projected to reach $4.8 billion in 2022, proving that businesses are rapidly adopting document processing technology as the necessity for automating complex use cases continues to grow.Īnd there are no signs of this growth slowing down. In the last few years, intelligent document processing (IDP) has seen rapid growth in adoption rate as organizations deal with high volumes of complex documents.
0 Comments
Leave a Reply. |
AuthorWrite something about yourself. No need to be fancy, just an overview. ArchivesCategories |