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Piles of Paper

Optical Character Recognition (OCR)

Digitalising your documents and making your data discoverable is an important step in your Digital Transformation journey

Data is the new oil. However, the value from your data can only be realised when that data is digitised into a format that supports further processing and analysis using digital tools like Robotic Process Automation (RPA) and Machine Learning (ML).

Digitization of data

What is Optical Character Recognition (OCR)?

Optical character recognition (OCR) is a data capture and digitisation technology that recognises texts in images and converts these images of texts into machine-readable text data.


Enhanced with AI, OCR-based technologies can intelligently recognise even difficult data like free-form, cursive handwritten texts.

In combination with technologies such as Machine Learning (ML), Deep Learning (DL), Natural Language Processing (NLP), and Computer Vision, OCR powers Intelligent Document Processing (IDP), turning unstructured data into structured data.

How does OCR work?

 1  Capture

Capture any type of document, electronic or paper, from any source


 2  Classify

Identify and sort the documents using machine learning (ML)

 3  Extract

Extract the metadata of documents using business rules and database lookups, fuzzy logic, etc. 

Find out information such as vendor names, invoice number, subtotal, etc.

 4  Validate

Users receive alerts on any error or exceptions. Allow manual overrides.

 5  Deliver

Automatically send data, on-premise, hybrid, or cloud

Connects to RPA, BPM, ERP, and more

Benefits of OCR and digitisation


There is no need to physically maintain and store paper records, which takes up large storage areas and tend to deteriorate quickly

Instant access to the most updated information

Having the most recent information at all times facilitates better business decisions


Data becomes highly accessible and can be retrieved quickly for use in different processes in the company

Visibility and availability of data

The availability of data across the organisation allows for analysis and optimization by different departments

Examples of automation use cases using OCR, RPA, and AI tools


Processing and following up on customer feedback

Capture large volumes of handwritten customer feedback forms


Automatically key customer feedback into the CRM


Understand and classify these feedback into different categories for follow up by the relevant departments



Invoice processing

Capture invoices of varying formats and extract the relevant information 

Tip: Use our free InvoiceBot service to do this


Automatically key invoice information into ERP system


Understand and classify invoices  for follow up by the relevant departments.



Application form handling

Capture large amounts of handwritten application forms


Understand and classify free-form texts like comments, interests, and other background information


Automatically enter relevant classification information into a marketing automation software for personalised lead nurturing


Do you need to know more use cases? Contact us.

Image by Douglas Bagg

Are paper documents getting in the way of your digital transformation?

Digitising your documents through OCR will allow you to make full use of RPA and AI  technologies

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