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Why OCR fails? 5 Drawbacks and Limitations of Conventional OCR Engines

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OCR Engine 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. Originally published at  infrrd.ai

Intelligent Automation for Financial Services

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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

Here is How Infrrd OCR Tool Is Making A Difference

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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...

How Can Adopting Intelligent Data Capture for Banking Sector be a Competitive Advantage?

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The reality is that Banks exchange a lot of information with other companies that they have no control over. They get annual reports from customers, they need to validate payslips for processing loans and there is no global standard for that. A lot of time they need to process collateral documents which comes in thousands of variations from a growing list of hundreds of providers. This can be possibly due to the unprecedented challenges faced by banks: from in-branch applications for accounts to cheques, loans, monthly statements, and other services, much of their daily activities remains mired in paper and manual processes. Also, Most banks have switched to online applications where they control the entry of the data. The challenge is for the documents that come from other companies that they do not control But, what’s the problem with papers? In today’s fast-paced consumer culture, delays become a liability to any industry that provides customer service. Cheques and forms have ...

The ‘Big Enough’ Data: Big Data For Small Business

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Thanks to its name and all the hype around Big Data, it gives a sense that Big Data is meant for big companies with a huge amount of data. It is generally believed that Big Data has nothing to do with small businesses that generate small chunks of data. True, Big data is changing the game for a lot of big businesses, but as an SMB owner, have you looked at how it can impact your  business ? Read on to find out how Big Data can work for ‘big enough’ data for Small-Medium Business. The answer might surprise you… THE ONE MINUTE ‘YOU NEED BIG DATA OR NOT’ TEST: Here’s a quick test for you to figure out if your business can benefit from Big Data Analytics: Does your business use computers to store business data? Do you exchange information with your partners, customers or employees using electronic media like documents, emails, etc? Do your employees, users or customers talk about your products or services on social media? If you are running a Small to Medium business in 20...

Image Classification- Why Identifying Images Is Not Enough

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The need for making sense of images and extracting meaningful insights from them seems to be rapidly growing. Images are the second most popular content type and there is a vast range of companies that deal with images in one form or the other on a regular basis. This spikes up the need for better  image classification  with increasing accuracy and using automation. At  Infrrd , we dealt with one such use case where the customer wanted us to build a platform for a user to sell his / her watch. In this case, a user uploads an image of the watch he wants to sell. This system eases the user’s work by correctly identifying the watch and auto fill all the details about the image and upload it to the site for sale. Our system needed to do the following: given an image, identify and recommend similar models and finally, classify the watch to the right model. Robotic Automation What most recognition platforms can do: Given an image of a meeting room, they can ide...

Conversation with a Canvas - What makes Infrrd Intelligent Data Capture (IDC) better than OCR?

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Intelligent Data Capture  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. Infrrd’s  Intelligent Data Capture (IDC)  implementation can help and make a significant impact on operations and workflows with near-perfect accuracy. It’s prolific and definitely the next big thing that’s gaining major traction in the enterprise environment. But this is just a tip of the iceberg. Adapting IDC provides a single point of access for all of your business information. Despite numerous advantages, decision makers still think twice about why should one invest in IDC? If you’re one among them  contact us  for a  free demo  today and get your questions answered about IDC or business-specific applications. Originally published at  infrrd.ai