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  • Maris Kolesnikovs

Extracting data from documents using Intelligent Document Recognition (IDR)

The typical office worker reads more than 10,000 pages of documents a year, with 45% of those being useless after just one day.


Also, the average worker spends 30–40% of their time looking for specific documents or bits of information.


Want to avoid this for your company?



Processing Data

Intelligent document recognition (IDR), which uses AI, can sort and handle different types of unstructured and semi-structured information found in documents.


AI and optical character recognition (OCR) are often used together by IDR to analyse data as quickly and accurately as possible.


Every business activity involves documents, and more than 80% of the information they hold is trapped or buried.


IDR is important for any business that wants to grow because it helps businesses understand their data better and make better business decisions.


Some companies are aware of these problems, but most of them find it hard to digitise their data in the right way. And no, scanning a document and creating a PDF from it is not the best course of action.


Making things Worse

The truth is that most companies do use the scan, copy/paste, and convert to PDF procedures; nonetheless, most of them will end up searching on Google for simple ways to extract data from PDFs.


Because people aren't perfect, well-tuned robots, and because these methods are expensive, take a long time, and can go wrong,


However, these procedures may now be fully optimized for any organization looking to step up their game, enhancing accuracy, speed and drastically lowering errors, owing to intelligent document recognition (IDR).


Almost any type of vendor can use IDR to quickly connect data that has been extracted to other business systems like RPA, ERP, or CRM.



How does IDR function?

  • Document classification:

IDR can find patterns and information on a document and put it into different fields.


If the word "insurance" appears more than once in a document that the system is looking at, for example, it may figure out that the document is about an insurance policy.


When done by people, document classification is a laborious process, which is why IDR can be a great long-term fix.


  • Data extraction:

IDR automatically extracts pertinent data points from documents after they have been classified.


The data points for each firm vary based on what they want to extract from their document sets.


Most of the time, a person will need to give the system a large sample size so that the software can learn how to get accurate data from it.


  • Data validation:

Before coming to a conclusion, the system will check that all the extracted data is correct and consistent.


This method is often paired with "human-in-the-loop," in which a person decides at the end what the machine should check.


Make an appointment for a free demonstration with one of our document solution specialists to see how IDR applies to your documents.


Benefits of IDR

IDR is a good choice for businesses that have trouble with complicated back-office processes and want to simplify their operations in the long run.


  1. It automates data entry and extraction while assuring high accuracy, so it can work around the clock without becoming fatigued as we do.

  2. It uses smart validation processes that make it much less likely that data will be wrong, which would be common if a person did the work by hand.

  3. The program reduces the significant expenses that are typically associated with fixing errors and paying fines for noncompliance.


How quickly can IDR be put to work?

Most people think that integrating AI-based software will be hard and take a long time, but the reality is very different. IDR is easy to add to any system and can often be done without the help of IT experts.


Ending Note

People are amazing, but we get tired quickly, especially when we have to do the same things over and over.


Employees can concentrate on other tasks because data processing takes a lot less time than it would with a team member.



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