Infrrd AI Enabled Intelligent Document Processing for Complex Documents

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...

When receipts come in different sizes, layouts, and formats, the manual method can break down. Employees can grow bored doing repetitive tasks and become disengaged, leading to unexpected and costly errors.  Worse yet, errors can trigger rework that steals even more of your employee’s time and productivity.  This calls for a smart solution that can effortlessly automate repetitive tasks so employees can spend their time on things that truly matter, doing things that only humans can do well. Modern solutions can also increase efficiency and quality by automatically doing real-time policy checks, detecting duplicate and fraudulent bills, and more.  And the solution is…. Automation. But hold on, all data extraction solutions aren’t the same. For example, consider  OCR . It’s an old but reliable horse in the race of automation and many businesses use OCR today to extract data from documents. But OCR has its limitations - especially when it tries to tackle complex...

Signatures are seen everywhere - in Art, Cryptography, Music, Bank Cheques, etc. It is a mark of a person for a proof of identity and intent. It is distinctive and unique to that person. It’s also a way to confirm the person's identity. Although it is unique and private to that person, it can be forged. Banks use the signature to verify the cheques, Cryptocurrencies use the digital signature to verify a transaction, Art museums use the signature to identify the art’s owner. Hence, identifying the authenticity of the signature is of utmost importance. This is where the  automated signature validation  becomes important. In the past, people used to manually do signature validation. Wherein, the bank’s employee would authenticate the signature on the cheque, Art museum’s employee would authenticate the signature on the art and so on. This requires a good eye to notice any subtle differences and is prone to error. Also, it is quite a time-consuming process. ...

WHAT IS OCR? Data entry can often turn tedious and inaccurate if done manually. But, you can avoid this cumbersome process with an automated optical character recognition software. What OCR does is, it uses machine learning to scan each character on a page individually. It allows the documents to upload as text documents instead of images. We could scan easily and promptly any kind of printed document, be it receipts, invoices, contracts, utility bills and much more with this solution. HOW IS INFRRD’S OCR DIFFERENT FROM TRADITIONAL OCR? Our  OCR solution  is different in two ways: We don’t use templates but NLP for recognizing entities in a document. This helps us identify business names, bank details, amounts, prices etc. irrespective of where they occur in the document. Read more  here  on why templates are a bad idea. We use Machine Learning to fix what traditional OCR’s cannot figure out, by building an automatic context around the...

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...