Infrrd AI Enabled Intelligent Document Processing for Complex Documents

  With rising home sales in the US and increasing demand for the use of technology in the mortgage approval process, IDP-driven end-to-end automation is expected to make a significant impact in this space. Because processes in mortgage origination are labor-oriented, automation and IDP are more impactful and beneficial for the mortgage industry than for most other Industries. According to the  McKinsey & Company report, A Future that Works: Automation, Employment and Productivity , “the value of the potential benefits of automation, calculated as a percentage of operating costs, is more than 90 percent for mortgage origination.” Moreover, this report says it takes an average of 37 days to approve a mortgage application in the U.S., of which about 14 to 21 are spent on the mechanics of application processing. With IDP, this could potentially drop to under six days. Mortgage automation is the key to a great customer experience The last few quarters have seen one of the large...

Infrrd was recently recognized by Everest Group as a Star Performer and Major Contender in the consulting and research firm’s “Intelligent Document Processing (IDP) Products PEAK Matrix® Assessment 2021.” It’s exciting for us because it highlights our momentum and market impact. We’re very proud of both, and delighted to be part of an industry that’s exploded as the need for automation became blindingly clear.  Read the complete article

Intelligent Data Processing Automating data extraction from complex documents  has been a challenge for so many for so long. Maybe you tried using OCR to automate data extraction.  It works for more simple documentation.  Perhaps you were successful using cloud tools from Amazon or Google to automating more simple stuff, and figured,  “What the heck, we’ll try that for the complex stuff, too!” Have you ever wondered about  99% accuracy  of data extracted from 𝗰𝗼𝗺𝗽𝗹𝗲𝘅 𝘁𝗮𝗯𝗹𝗲𝘀? Answer these 5 questions to find out.                         READ MORE  ….

True or false? Extracting data from Annual Reports is time-consuming. Extracting data from Annual Reports is painful. Extracting data from Annual Reports  has to be a mostly manual process. If your company is like most in need of the data trapped in Annual Reports, odds are you called all these statements true.  But, what if you’re mistaken? There’s a reason most find  extracting data from annual reports  difficult, time-consuming, and/or costly. Because until recently, the common ways to address the challenge were inadequate. Intelligent Data Processing                          READ MORE 

There’s  tremendous value  trapped in your unstructured data, complex documents, and images.  Extracting it manually is slow, expensive, and doesn’t scale well.  OCR has its performance limits and eventually hits a wall.   How can you  remove this bottleneck?    This ebook is an executive guide to  Intelligent Data Processing , a new AI-driven solution that can  unlock the data  you need to drive intelligent automation and improve business processes.   Get an overview of  IDP , explained in simple terms.  Learn what it is, why it’s  fundamentally different from OCR , and how it can be applied to remove bottlenecks in your business. Includes three examples of  typical use cases .  Get Your Free Copy here to know more :  https://hubs.ly/H0n1Qfs0

Infrrd’s IDC   is a single platform that meets all the organizational needs of data capture from structured and unstructured sources to achieve business process automation to increase productivity and reduce costs. Infrrd saw an opportunity to use AI to improve existing data extraction processes and developed our advanced  I ntelligent Data Capture (IDC) technology . IDC combines five AI technologies to deliver automation that can sense and synthesize vast amounts of information necessary to automate entire processes or workflows. ​ The IDC platform not only eases data extraction but also addresses challenges of accuracy, time-management, and performance. The platform uses Machine Learning capabilities to identify and extract critical fields and line items such as date, vendor name, payment type, city, state, tax, and total, irrespective of any templates with high precision.  Machine Learning also enables the platform to learn, adapt, and improve as you acquire more dat...