OCR vs. Scanning – How are OCR Document Scanners Better?

Ashutosh Saitwal
Ashutosh Saitwal

Founder CEO - KlearStack AI

Table of Contents

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Say no to Paperwork by Saying Yes to Intelligent Scanning with OCR

What do people do when a physical document needs to be digitized? Scan it, of course!

But scanning using standard equipment has its limitations. You can scan a document and convert it into an image or doc file, but you can’t edit or manipulate the data in any way once it is digitized. If you catch errors, you’ll have to go back to creating a rectified physical document and then re-scan.

Now imagine going through this process with high volumes of data and the paperwork that follows them. Not only will these loads of paper create confusion, but they will also reduce efficiency, increase costs needed to store them properly, and consume manhours that can be used elsewhere.

Once the paper documents are scanned, if you want to capture data in an editable format, you need Optical Character Recognition (OCR)OCR technology provides a much more sophisticated output compared to scanning as instead of capturing the document as an image, it identifies the characters and converts them into machine-readable text. This process allows you to edit the text, search for keywords, and retrieve information faster.

OCR document scanners are widely used as data entry solutions for documents like bank statements, computerized receipts,  invoices, and purchase orders, etc. OCR, by itself, has constraints when it comes to advanced data capture and interpretation. It can effectively convert text from physical paperwork into editable text. Still, it cannot provide an intelligent mapping of that data. Thus the final output is unstructured and requires manual man-hours if you need your data in a structured format. We need Artificial Intelligence and Natural Language Processing (NLP) to help advance the technology.

That’s where Intelligent Data Processing (IDP) comes in. IDP works with Neural Network, OCR, AI, Natural Language Processing, and Machine Learning to make systems produce advanced analytics for more accurate data extraction.


Intelligent OCR Scanning: A Better Way to Automate Business Processes

OCR technology has existed for a while now. If you have scanned documents and used them digitally as a doc file, you have used OCR.

But what makes the technology better is the combination of hardware and software and the use of Artificial Intelligence. AI-driven technology is a fast progressing revolution, and OCR scanning coupled with AI, has already shown so much development.

From being able to recognize text regardless of the style and font, to be able to understand the context of the document being scanned, OCR, with NLP and AI (Intelligent Data Processing) is a complete solution for all data extraction needs. Specialized IDP solutions (like KlearStack) can even return output from physical documents in a structured format. Hence, reducing the need for a human role in data extraction by a huge margin.

Initially, the output from even the smartest OCR solutions requires human monitoring. This ensures that any errors made by the machine are rectified before they are permanently stored in the system. That said, these systems leverage machine learning to automatically learn from past human rectifications. It adapts to the changes made to the output to perform a better job in future documents. Thus, reducing to need for monitoring and chances of errors over time.


Optical Character Recognition vs. Scanning


Traditional OCR  Intelligent Document Processing
Data extracted is converted into machine-readable text that can be edited. The document image is not only converted into machine-readable text but is also interpreted to derive document insights and structured data
Doesn’t work on comprehension Through Machine Learning and NLP. texts can be scanned with context
No error correction Because of context comprehension, anomalies are detected for rectification
Time-consuming labor and costly paper storage Digitally stored data. Information can be retrieved instantly
Manual processing required for data entry Data extraction, interpretation is automated


About KlearStack

With our proprietary IDP technology, KlearStack is the best possible end-to-end solution for all the data extraction needs of your accounts payable and receivable departments. The platform is template-free and can intelligently extract data from documents like invoices, purchase orders, and receipts – including line items.

The software focuses on eliminating human efforts, so your team can focus on matters that need more attention.


Conclusion :

It’s high time that organizations across all domains and irrespective of the organization size should adopt such AI based tools to reduce the wastage of resources and leakages in the cash-flow.


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