Machine learning is the science of getting computers to act without being explicitly programmed. It is based on the idea that machines should be able to learn and adapt through experience.
In the past decade, machine learning has given us self-driving cars, practical speech recognition, effective web search, and a vastly improved understanding of the human genome.
When it comes to the day to day challenges that virtually every knowledge worker in any business faces when working with documents and data, machine learning has a lot to offer. Without self-learning technologies, the process of configuring software to automate the handling of documents and extraction of information historically made sense only for large volumes of similarly-formatted files.
Today, with digital transformation technologies like AI and machine learning embedded in what is known as an intelligent document processing software, a wide range of documents-dependent business processes can be automated to eliminate document sorting/filing, document matching, error checking, data entry, routing and approval - all with minimal human intervention.
Today’s digital transformation technologies incorporate machine learning to handle a wide range of unstructured data trapped in scanned paper or digital documents and correspondence.
These technologies allow a company to:
Artsyl focuses on intelligent document processing for solving the most painful, manual steps in common business processes; document handling and routing, transaction data entry and validation and reports/process monitoring.
By relying on Artsyl workflow automation solutions for extracting data from scanned paper documents and electronic files, customers achieve more timely access to data and can automatically eliminate duplicate documents/data.
InvoiceAction is an AP automation software that minimizes the cost, complexity and time required to implement complete accounts payable automation for vendor invoices.
OrderAction is an order processing software that automates and streamlines sales order processing, delivering more complete, timely buyer behavior data while reducing order cycle times and days sales outstanding.
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