Infrrd AI Enabled Intelligent Document Processing for Complex Documents

  When we started our IDP business, our assumption was that cost savings would be the main driver for purchasing decisions - in other words, how we can help our customers save 30-50 percent on data processing costs. But the last six years have taught us those cost savings are the number two priority for most companies looking for  IDP solutions . Read the Complete Article

  Most people think that  Intelligent Document Processing  (IDP) systems are used by companies to primarily save costs. Our experience with some of our leading financial services customers has taught us that this is not usually true. The number one problem that most companies try to solve with IDP is scalability. How can they enable their teams to handle a higher volume of data more rapidly? How can they offer better response times or reduce SLAs for their key customers? While most of the heavy lifting of processing documents is done by the IDP system, you still need a data processing team to handle exceptions. As you scale your business, you often need to add more people to the team. Read the complete article

All Intelligent Document Processing begins with a document - a collection of one or more pages. Pages from the basis of all the processing that the IDP platforms perform to make sense of data. Though most of the focus of ‘intelligence’ in IDP refers to how you make sense of data, you will be surprised how much Intelligence is used on a page before it is ready for data extraction. I am not talking about things to do with scan quality such as your skew correction, resolution improvements or shadow removal, etc. I am talking about things to do with the basic anatomy of a page. Stuff that begs the question, “What is a page, anyway?” Read the complete article

  The  IDP  market is going through an interesting phase - a lot of new players have entered the market and all of them make similar claims about their AI and use of Machine Learning Technologies. We have worked with customers who were led to believe that they are using an AI platform for IDP but found out very late in the process that the product used very minimal machine learning. Just enough to give them a check in the box that they are using ML but hardly enough to make a difference for the customers. Read the complete article

In keeping with our spirit of continuous learning and improvement, we made some great upgrades to our  IDP platform  over the summer. As you know,  Infrrd  empowers our clients with solutions for intelligent work that take advantage of end-to-end process automation, a critical part of which is automated data extraction. Our intelligent document processing (IDP) platform leverages a machine learning (ML) model that any user can use to create a powerful data extraction solution delivering efficiencies and cost savings far beyond the reach of standard  optical character recognition  (OCR) systems. Data extraction can get extremely messy and necessitates human-in-the-loop intervention to improve the efficiency of the algorithm, although ensuring 100% accuracy can be a challenge. Our improved Audit feature addresses this aspect by making it easier for users to extract and review corrected data. Read the complete article

  This past month, the Infrrd team collaborated with our client, a large financial institution that has a team of about 100 people extracting data from documents manually. This customer processes a huge variety of documents from numerous sources that do not have any fixed format. Every document from every provider comes with its own unique layout and vocabulary of information. These documents arrive at the firm’s mail room where they are combined into packets of hundreds of documents then get handed off to the data processing team. In all, the customer has millions of combinations of layouts from which the team extracts data. Read the complete article

A System For Extracting Data from Complex, Unconventional Images Where Traditional OCR Solutions Fail As the CEO of Infrrd, I am committed to continually pushing the boundaries of innovation so that we offer the most comprehensive and transformative solutions to our customers. In fact, we created the Infrrd Research Lab whose mission is to solve the toughest problems our customers face, as well as to ensure we are the leader in AI. From global insurance to mortgage lending to healthcare organizations, companies need powerful solutions to extract, manage and glean predictive insights from valuable customer data, leveraging the most powerful AI and machine learning-based solutions. As a result, they radically transform their business as they can better scale their operations, provide a superior customer experience, bring new efficiencies to their workforce and processes, and substantially lower costs.  Read the complete article here