Infrrd AI Enabled Intelligent Document Processing for Complex Documents

If data is the new oil then accuracy is its Octane Number. Companies may have hundreds of disparate sources of data – spreadsheets, documents, receipts, invoices, RFP’s, financial reports etc. , if not scraped through accurately that would be a major show stopper. Manual scraping is time consuming and laborious, while un-intelligent  data extraction  tools will require human intervention to monitor and make corrections. Need of the hour is an Intelligent Data Capture platform that drives contextual accuracy like a human . Accuracy is one of the most important aspects of data extraction. Originally published at  infrrd.ai  

Infrrd’s current wave of technologies has tested a multilayered extraction model successfully that employs a suite of advanced  AI-technologies  to streamline the operational process. This is a result of a months-long effort in finding the right composition of technical modules. The following details provide a bird’s eye view to the multilayer architecture and its capabilities. Originally published at  infrrd.ai  

While conventional  OCR engine  is considered as a mainstay platform and might seem like the end-all, be-all solution for capturing data. It can be frustrating at times when the data is misread or not even be read. Inputting a document into an OCR doesn’t mean that it will actually output something without a hitch- forcing knowledge workers to manually work. Why does OCR fail? Many OCR engines fail to support and understand the complexity of the input data in a given document. For example, if the input document is a form then the OCR might identify the text but may not recognize text over a line or the text in blocks. This may result in unexpected output. Originally published at  infrrd.ai  

Many multinational companies today, face the most significant revolutionary change in the realm of technology. Namely, conversion of paper documents to digital and the inability to leverage data ensnared inside scanned documents and images. Relying on data trapped inside documents and manually re-keying them can land businesses into a bottleneck situation. Therefore, the need for an automated solution to segment and extract document elements is high.  Originally published at  infrrd.ai  

Whether you’re presenting an annual report, comparing sales figures, or highlighting a trend, visual representations such as graphs or charts are a great help to understand data elements quickly. However, in today’s hyper-interactive world, it’s hard to understand why data still continues to be represented as colorful graphs. These data trapped visual representations that cause restrictions in harnessing the data or make better decisions. Originally published at  infrrd.ai  

Whether qualitative, quantitative or temporal dataset, a tabular presentation has always been a systematic yet logical way to represent data. As data increases at unprecedented rates, the struggle lies in binding data-enriched tables to paper-centric sources. Also, the difficulty with these paper-centric documents is that it limits the capability to automatically extract and interpret insights computationally for future use. READ MORE .......

Data extraction  from unstructured documents is a complex  task.We  can overcome this problem with help of Intelligent Data Processing. Data Extraction From Complex Documents Benefits of Infrrd’s Intelligent Data Capture platform: Effort Reduction:  The IDC platform is well-equipped with cognitive capabilities that makes self-learning feasible and adapts different layouts, configuration, rules, or templates. This saves a great deal of effort. Time-saving:   IDC solutions  can process graphs 12x times faster than humans letting employees work on value-added tasks. High Precision:  Through self-learning, the module learns to become more efficient and reduces human-ridden errors leading to more accurate and faster results. Increased Productivity:  With  IDC  in place, it’s possible to perform graph extraction in less time with reduced errors. This means less double-checking and reworking tasks, leading to higher efficiency and productivity. Moreover, the business processes w

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 :  https://hubs.ly/H0pqkpt0

How AI can Solve your OCR Problem The success of your  Intelligent Automation  strategy depends on your ability to extract necessary data from paper-based documents such as contracts, manuscripts, books, invoices, receipts, etc. and convert it into machine-readable text.  Unless you want a manual data entry bottleneck in front of your whole automation process, step one of your automation strategy should include the automation of that data extraction process.                                         READ MORE

Intelligent Data Processing The technology that enables us to extract information from scanned images of printed or handwritten documents is called  Optical Character Recognition  or OCR.  Accurate and reliable data extraction  plays an important role in finance, accounting, electronic health record updates, insurance claims processing, personal and national security, logistics documentation, and legal documentation.                                       READ MORE