Infrrd AI Enabled Intelligent Document Processing for Complex Documents

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. Following details provide a bird’s eye view to the multilayer architecture and its capabilities. 1. Computer Vision As an intense lens can recognize the objects well and spot loopholes, the vision also plays a similar role. It recognizes and identifies the regions of the document that needs to be extracted. It performs preprocessing operations to improve the quality of the document by distinctly identifying the text, images, stamps, handwriting, etc and make it ready for extraction. Also, the document is classified by understanding the structure of the document pages. Intelligent Data Capture At  Infrrd , we’ve done intense research on identifying various objects on a page/image. Our ...

Data analysis without data preparation it is a myth. Unless we feed the right data in a proper format, Machine Learning algorithms won’t be able to solve our problem. If we give one wrong input then we end up where we started. So it’s very important to understand what data preparation is and how one can do it. Data, in its original form, may have a lot of missing pieces or disarrangement. Through data processing, one can modify this raw information from a specific database to a format which is understandable and learnable by the machine. Mentioned below are the ways that, we at Infrrd , employ in preparing our data. 1. Data selection: It is necessary first to identify the type of data we are going to be working with. One has to keep in mind whether the available data will be able to address an existing problem or not. We keep certain factors in consideration before selecting the data: Data should not be of low quality: Low-quality input= low-quality output. Dataset is not err...

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...