Infrrd AI Enabled Intelligent Document Processing for Complex Documents

  Artificial Intelligence Machines learn like humans “Just think how we have learned to understand something, or how we have learned to infer something,”. “That’s the evolution of intelligence a human being has, the same thing happens with a machine, also, so slowly they start learning things, slowly they start understanding things, and in that way, they can start inferring things, and that inference is what can lead to machine learning, or we can say,  artificial intelligence .” Priya Thampi ,  VP Engineering Explains – Why customers believe in  Infrrd ’s  approach and how Infrrd’s technology is making a difference from others. READ MORE

                                AI Technologies Someone has to pay the price for your AI failure. Let it be your competitors.  A back-office supporting the insurance industry processed millions of documents every month, relying on a small army of manual data entry specialists.  This manual process was expensive, time-consuming, and difficult to scale fast enough to accommodate their growth. Every time they hired a new employee, it took about a year to train them to the point at which they were “fully productive".This company needed an  AI solution  to automate this process.   Did your  AI  implementation fail in 2019? Find out how enterprise companies made spectacular recoveries after their AI failures.                           ...

I spotted another interesting question on Quora related to  machine learning & OCR , here’s my answer: I will give you a consultant’s answer – you may not like it but here goes – “It depends”. The ‘best’  OCR extraction  method depends on the context of what you are trying to extract. My guess is that you are not talking about the OCR process itself. But, rather how to extract features out of the text that OCR spits out. ​There are two broad approaches for extraction depending on whether you know the kind of data you are dealing with (invoices, tax docs, grocery labels, etc) or you do not: DOMAIN-BASED OCR EXTRACTION This approach helps when you know beforehand the kind of data extraction you are after. Let’s say you were trying to extract features of wines from a set of wine ratings and notes that you have OCR-ed. Before you can do the feature extraction, you may consider running topic modeling algorithms on a large collection of existing wine notes to fig...

Why waste time and resources on tasks that can be automated with technology? 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. Intelligent Capture for Accounts Payable Get a   free demo   to know more Intelligent Data Capture technology

When introduced,  Optical Character Recognition software  was considered to be a boon for businesses. Instead of manually transferring data from records, one could now simply extract data from them. Later they can enter it automatically into in-house systems. We can save hours of manual labor but there remains a caveat. Errors introduced during the extraction process remain in your system. Before we recognize and fix the errors it can stall the work for many hours. OCR scanners are prone to fail when one tries to extract data from old documents. Either the fading of the print or the lack of contrast can lead the software to incorrect recognition of patterns. Additionally, most online  OCR software  is designed to work with English as a language. But not everybody uses English as their first language. If you travel to Europe, the script remains the same but the language differs. A smart engine OCR should be able to pick up this difference in language and adapt its...

When introduced, Optical Character Recognition software was considered to be a boon for businesses. Instead of manually transferring data from records, one could now simply extract data from them. Later they can enter it automatically into in-house systems. We can save hours of manual labor but there remains a caveat. Errors introduced during the extraction process remain in your system. Before we recognize and fix the errors it can stall the work for many hours. ​ OCR scanners are prone to fail when one tries to extract data from old documents. Either the fading of the print or the lack of contrast can lead the software to incorrect recognition of patterns. Additionally, most online OCR software is designed to work with English as a language. But not everybody uses English as their first language. If you travel to Europe, the script remains the same but the language differs. A smart engine OCR should be able to pick up this difference in language and adapt its data extraction algori...