© 2025 Dost All rights reserved.
Optical Character Recognition, commonly known as OCR (Optical Character Recognition), is a technology that has transformed the way we interact with physical and digital documents. OCR is a tool that interprets physical text or images and converts them into digital data that can be processed on your computer.
Imagine the typical scenario in an office: mountains of printed documents, invoices, contracts... waiting to be digitized for storage or processing. This is where the OCR comes into play. OCR allows you to scan these physical documents and automatically extract the text contained in them, thus eliminating the need to manually transcribe each word.
The concept of character recognition dates back to the 1950s and 1960s, when people began exploring ways to teach computers to interpret printed text. These early systems were rudimentary and based on predefined rules.
In the 1970s and 1980s, OCR began to gain traction as a tool for converting printed documents into digital format. OCR systems of this era were capable of recognizing a very limited variety of fonts and text styles.
1990 marked a turning point in the development of OCR, with significant improvements in recognition, accuracy and speed. More sophisticated algorithms based on neural networks and machine learning were introduced.
With the arrival of Artificial intelligence techniques in recent decades, OCR has experienced a revolution. Now, software like Dost is capable of enhancing the work of OCR and achieving levels of precision and speed never seen before.
OCR presents a series of very important benefits and advantages for your business, and especially for your financial and accounting departments. Here we leave you some:
Much of the information we handle is still in print, from legal documents and invoices to books and magazines. OCR allows us to quickly convert these documents into digital format, making them easy to store, search and access from anywhere and at any time.
Automation is the key to increasing efficiency in any digital environment. OCR allows us to automate tedious and repetitive tasks, such as manual data entry, form processing, and information extraction from documents, thus freeing up time and resources for more productive activities.
Speed and precision are essential in the digital world. Modern OCR systems are capable of recognizing and processing large volumes of text in a matter of seconds, with accuracy rivalling that of humans. This allows us to accelerate and minimize human errors in data entry.
OCR also plays an important role in promoting digital accessibility and inclusion. It allows you to convert printed documents into formats accessible to people with visual disabilities, such as text files, or audiobooks, thus opening access to information to a broader and more diverse audience.
In a business environment, efficient document management is critical to success. OCR allows us to organize and categorize documents intelligently, facilitating their search, recovery and analysis. This not only improves productivity but also helps in making more informed and strategic decisions
OCR with artificial intelligence (AI) represents the latest and most exciting evolution of this technology, taking it to new levels of accuracy and versatility. Unlike traditional OCR systems, which relied heavily on predefined rules and pattern recognition algorithms, OCR with AI uses machine learning models to understand and process text in a way that more closely resembles the human brain.
The first step in operating OCR with AI is training artificial intelligence models using large text data sets. These data sets contain a wide variety of fonts and text styles, allowing the model to learn to recognize and understand character patterns with unprecedented accuracy.
Once the AI model has been trained, it is used to extract key features from text images. This involves identifying and highlighting areas of interest in the image, such as words and letters, and transforming them into numerical representations that can be processed by the model.
The next step is pattern recognition, where the AI model analyses the extracted features and looks for similarities with the text patterns it has learned during training. Using advanced image processing and neural network techniques, the model can identify and classify characters with exceptional accuracy.
As the AI model processes the text image, it may encounter errors or inconsistencies in character recognition. To address this, error correction and refinement techniques, such as linguistic context and user feedback, are used to improve the accuracy and quality of the final result.
Digitizing documents and files is one of the most practical and beneficial applications of online OCR in the digital age. This technology allows us to convert physical documents into accessible digital formats, which not only simplifies their storage and management, but also opens up new possibilities in terms of search, collaboration and information security.
The automatic extraction of data from forms is one of the most valuable and efficient applications of online OCR in the business and administrative field. This technology allows us to quickly digitize and process information contained in physical or digital forms, eliminating the need for manual data entry and reducing human errors.
Online OCR not only simplifies the conversion of printed documents into digital format, but also greatly facilitates the search and analysis of the information contained in these documents. This search and analysis capability is critical in the digital age, where rapid retrieval and understanding of information is essential for informed decision-making and business success.
Automated invoice management is crucial to optimizing a company's financial processes. Eliminates the need for repetitive manual tasks such as data entry, thereby reducing errors and increasing efficiency. Additionally, it allows for more accurate tracking of invoices, ensuring they are paid on time and avoiding potential penalties for late payments. Automation also makes it easier to comply with tax and accounting regulations, ensuring that all records are up-to-date and accurate.
AI OCR streamlines the billing process by eliminating the need for manual data entry. Using advanced character recognition and machine learning algorithms, OCR can automatically scan and extract key information from invoices, such as dates, quantities, and invoice numbers. This significantly reduces the time required to process invoices and minimizes errors associated with manual data entry. Additionally, AI OCR can learn and adapt over time, improving its accuracy and efficiency with each invoice processed.
Invoice automation with OC reduces operational costs by eliminating the need for manual labour to process invoices, allowing you to allocate resources to more strategic tasks and focus on business growth. Additionally, automation improves accuracy and consistency in invoice processing, reducing the risk of errors and discrepancies in financial records. Improve decision-making with more accurate and timely information. Additionally, invoice automation with OCR improves visibility and control over the billing process.
Of course, you can add information by correcting the extracted fields. To learn how to do this, please refer to the user guide on YouTube.
Yes, you can export documents in .csv, xslx and json formats.
You can export the general information of the processed documents, a graph of the optimized time, the data related to the economic savings by using our software and the classification of the types of processed documents.
Of course, you can delete any documents that you have not yet processed and that are incorrect.
If a document gives you an error, it will not be counted among the processed documents. You will have to try to upload it manually. As a last option, you can open a support ticket.
Any file in JPG, TIFF, PNG or PDF format will be valid for our artificial intelligence.