IDP can save time and workforce resources as it improves data capture by reading, analyzing, and converting content and documents into structured, searchable, and organized data.
Semi-structured data can be converted into structured, usable information, providing end-to-end automation to document-centric business processes.
Without IDP solutions, RPA automation processes need human workers in the loop to read documents and extract data. IDP is key to scaling automation. Key features include predictive modeling, natural language processing, image recognition, deep learning, and model training.
The Everest Group defines Intelligent Document Processing (IDP) as any software product or solution that uses AI technologies such as computer vision, OCR, Natural Language Processing (NLP), and machine/deep learning to capture, categorize, and extract data from documents for further processing.
IDP offers a powerful means to improve operational efficiency while driving down costs.
Together, IDP and RPA provide a simple yet effective tool to automate enterprise business processes.
IDP offers a powerful means to improve operational efficiency while driving down costs.
Across all industries, businesses are facing pressure to do more with less—and do it faster than ever before. At the same time, more organizations are focusing on removing friction from customer experiences and improving outcomes for employees as a key to improving revenue, margins, and retention.
IDP can be easily confused with robotic process automation (RPA) or optical character recognition (OCR). Perhaps you have also heard IDP called Intelligent Data Processing. Since documents contain data, these are sometimes used interchangeably. These documents arrive from sources such as email, text, and pdf. IDP can convert scanned pdf or document photos to editable words and usable data.
RPA is focused mainly on task automation within defined processes. These processes run on data, and your unstructured content is oftentimes the source of this data. For true transformation, it’s essential to understand the content in context before data can be extracted from it for various downstream processes.
IDP goes far beyond the capabilities of legacy OCR, which converts text from bitonal imagery to a machine-readable format. But it is limited in its application. In comparison, IDP encompasses a more comprehensive treatment of converting unstructured content into actionable data.
By applying pre-trained, out-of-the-box AI document skills in a way that supports the way humans understand and manage content, IDP saves time and money while also reducing the risk of costly errors.
While RPA and legacy optical character recognition (OCR) templated approaches to document process automation work well with highly structured data, where the expected data is in the same place every time, RPA and legacy OCR have difficulties handling unstructured data – such as email, Word documents, images, PDFs and more.
A true intelligent document processing solution needs to be able to incorporate document process automation that will handle any type of data: structured, semi-structured, and unstructured.
Using Intelligent Document Processing with RPA is what enables business users to automate processes end-to-end. When IDP and RPA live together in the same platform, you have the biggest pieces of the automation puzzle working in sync, effortlessly.
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