Below you will find a glossary that lists and defines essential terms for understanding and making the most of intelligent document automation.
Every business department involves document management, which is necessary to record information, communicate with customers and suppliers, and store important data. If done manually, these activities expose the company to numerous risks.
Errors due to manual data entry come at a significant cost to companies. It is important to invest in reliable data entry processes and proper quality controls so that errors and subsequent costs can be remedied.
Customer onboarding is the process by which a company introduces a new customer to its product or service. The following article explains what digital onboarding is, its automation, and its benefits.
Digital transformation includes implementing innovative technologies and redefining business processes to automate.
Many companies still manage expenses manually, causing low employee productivity. Today, expense management can be automated, reducing time, cost, and repetitive tasks that cause frustration.
Intelligent Document Processing refers to a set of tools and solutions based on deep learning techniques that can automate the processing of all types of documents.
Processing utility bills automatically is possible thanks to artificial intelligence. Specifically, the methodology by which all key information is extracted and obtained from utility bills, which is useful for various processes.
Document process automation has significant benefits for businesses. The following article discusses how automation overall improves all business productivity, specifically listing all the benefits.
The article discusses the expense report writing process and its main steps. Usually done manually, this process can be automated, and the article discusses its advantages.
In this article, you will find all the details about automatic document classification (IDP): what it is, steps in the process, classification methodologies, and advantages in using such innovative software.
The article examines the extraction of information from documents. The task is often performed with traditional solutions, which have many limitations. Modern solutions overcome these limitations and are adaptable to all documents.
The article outlines the difference between structured, semi-structured and unstructured documents. It illustrates the problems regarding the processing of all document types, solved by Artificial Intelligence-based solutions.
The article shows how to process ID documents automatically. Specifically, how to automate the extraction of information. This service is useful in many application scenarios and the company can benefit from it.
Companies still do manual data entry, causing quite a few problems. This process, nowadays, can be automated with modern technologies that avoid repetitive activity, cutting down time and costs.