Infrrd AI Enabled Intelligent Document Processing for Complex Documents

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 new  AI-driven  approach to data processing can do far more than OCR.  What is IDP?  Why is it different? When is it better? Is it right for me? 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.   Intelligent Data Processing 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 .  Download Now To Know More : ...

“Intelligent data capture can achieve up to 95% accuracy and processes 12x faster than manual processing.” While traditional  OCR solution  may still be a better option for a few organizations, it fails to address critical challenges of graph extraction like identifying trends. Moreover, it also fails to address issues such as identifying overlapping graphs or axis scales and labels. Unlike OCR technology, the  IDC  platform is powered with AI-capabilities like  Machine Learning  and Natural Language Generator (NLG) to analyze the full population of data and identify outliers and expectations. It is these capabilities that enable entrepreneurs to draw a broader and deeper set of insights from visual representations. Once all the rules are in place, the data is extracted quickly and accurately, thereby increasing productivity and reducing the number of keystrokes required to perform the graph extraction task.  Intelligent Data Processing Infrrd’...

Infrrd  came up with a unique approach. Our  ‘ Intelligent Data Capture’ (IDC) encapsulates advanced AI-enabled capabilities such as Machine Learning and NLP to trawl through reams of documents to detect, analyze, and classify tables. But it doesn’t end there. Next, the data is captured in digital format, which routes data throughout the business environment for future purposes. Originally published at  infrrd.ai

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...

Infrrd   has some exciting news to share with its users: we have just won two prestigious awards, Rising Star Award for 2018 and Great User Experience Award by FinancesOnline Infrrd OCR  has officially been reviewed and certified by FinancesOnline, an independent SaaS review platform that strives to create unbiased analyses in a bid to help businesses find the perfect solution that fits their unique requirements. Not only did Infrrd OCR garner a positive rating, but it was also certified with the  Great User Experience  award for 2018. The AI technology of  Infrrd OCR , according to FinancesOnline, is capable of efficiently extracting simple and complex data as well as key fields from various types of documents for hassle-free procurement of information. FinancesOnline was impressed that our AI Platform is powerful enough to capture data from IDs, passports, financial statements, custom PDF formats, and even hand-written forms and notes. These ar...

Does your OCR technology make sense of the data that is extracted? Traditional OCR technology provides less accuracy as it does not understand what is being extracted and hence a considerable amount of errors occur. To remove such errors it needs manual fixing which is time-consuming and will require significant resources. The AI-powered Infrrd OCR removes all such difficulties by implementing machine learning algorithms to understand the data that has been extracted and improves the output automatically. Thinking About Switching From Your Current data extraction technology To an intelligent one? Here Are 7 Questions To Consider First: 1. How accurate is your OCR data extraction? When it comes to choosing an OCR app, accuracy is one of the most important criteria. Infrrd OCR is different from other OCR software as it works on significantly improving the accuracy of the extracted data. It achieves this by learning from existing business records and extracting data in cate...

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/

A decade ago the volume-heavy, error-prone and sluggish business processes of mortgage companies that take up considerable human labor were still struggling to find a direction with the technological transformation. Automation has finally kicked in for the Industry. Not only have the mortgage companies become more efficient, but the decision making logic has also evolved with the application of robotics and AI. The focus is now fixated on automating tasks, minimizing errors & improving customer experience. With the introduction of  AI technologies  like machine learning, mortgage professionals have been meeting their targets while achieving better customer satisfaction. Most of the work which was reliant on manpower is now being done by computers. As a result, professionals can shift their attention to more strategic aspects of the job like managing problems and processing exceptions. Infrrd’s AI-led automaton is enabling mortgage companies to replicate human reason...

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...