Infrrd AI Enabled Intelligent Document Processing for Complex Documents

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 ada...

The  OCR  technology has become widely popular today. Existing workflows and business processes have improved a lot after companies started adopting it. Some have even created their own versions of it to achieve better results in terms of productivity. Although, increasing the OCR accuracy isn’t something which can be done overnight but one can definitely try to do so in due course of time. So how can someone fine tune their  Optical Character Recognition  engines gradually? Well, there are different ways to attain this goal. We at Infrrd keep in mind the following tips:    1. Accuracy is achievable at a character level.    2. Accuracy is gainable at a word level. On the character level accuracy, an OCR capability is judged on how often it can recognize a right character, rather than how often it identifies a wrong character. Similarly, word level accuracy means how frequently an OCR identifies a right word. Infrrd   OCR   ha...

With the e-commerce boom, entrepreneurs have learned that conventional strategies of visual merchandising or sales promotions won’t be able to sustain profits in the cutthroat CPG industry. Many retailers are already implementing AI and image recognition to deliver the next level of customer experience, bringing the dawn of a new era for the retail industry. According to Gartner, by 2020, 85% of customer interactions in the retail industry will be managed by AI. Product discovery, product recommendations & trend analysis are some areas for implementation of computer vision and image recognition. This article elaborates on how image recognition can be implemented by retail & CPG companies. 1. Auditing Product Placement: Customers are making key buying decisions at store shelves and companies have to use technology to stay ahead of the fierce competition or face extinction. Gathering key consumer information helps companies understand their needs better. Shelf ...

Intelligent Data Capture  technology by Infrrd leverages AI/cognitive capabilities for information collection and analytics & finds its application mainly in document processing. It provides meaning to text extracted from many forms of digital assets such as documents, emails, text files and scanned images. The following infographic illustrates the process of Infrrd's IDC platform. Automated Invoice Processing https://infrrd.ai/

Old school ways of conducting financial transactions are gradually bidding adieu. Automation, AI, and data analytical tools are taking over to ease the workflow. Everyone in the market wants to move ahead to enhance customer experience, deliver value, and obtain market share. So boarding the train of digital transformation has become the first choice for most companies. Now the question is what does it signify for the present and future of this industry? Adapt and adopt, these are the key terms for most companies who are walking in pace with the technological revolution. Finance being the people first sector is shifting its focus to make their customers’ personal lives better and easier. Businesses are prioritizing greater agility and higher quality for their overall process improvements. Some of the changes they are going through are: Making investments on technology which can support or expand their operating models, thereby making their processes responsive, effective, and d...

Identifying objects, images, handwritten texts, places, people etc have not been the most easiest in the past and manually it can take a lot of time. Unless you try a different approach such as  ​ enterprise AI - based  Image Recognition   platform from Infrrd. With our machine learning and computer vision infused technology, you receive details about the images in real-time to make smarter decisions based on these insights. If you’re wondering about how this technology benefits you then we have just the facts you need. It’s image tagging and classification feature can be immensely helpful in categorizing, browsing, and moderating the kind of images you wish to show on your corporate website. Our computer vision algorithms will tell you what’s in a particular image, whether an object of interest is present in an image or not, and whether it’s you need to extract that image or not.  ​ OCR The next feature is feature extraction and object detection. With this...

Infrrd provides Artificial Intelligence & machine learning solutions for document control, invoice data extraction, receipt data extraction etc for Real estate, mortgage, financial services, Banking & insurance. Infrrd Enterprise AI platform includes natural language processing, robotic process automation, image recognition, computer vision, and machine learning. Intelligent Data Capture technology   by Infrrd leverages AI/cognitive capabilities for information collection and analytics & finds its application mainly in document processing. It provides meaning to text extracted from many forms of digital assets such as documents, emails, text files  and  scanned images. The following infographic illustrates the process of Infrrd’s IDC platform.