Get text from PDF invoices to Excel quickly and cost-effectively

The versatility and flexibility of PDFs have made them the de facto official file format for document sharing and collaboration. However, converting data from PDF invoices into accounting tools can present a challenge. Let’s focus on how you can get text from PDF invoices into spreadsheet programs like MS Excel.

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Get text from PDF

In the late 1990s, there was no widely used standard for the cross-platform exchange of documents. This meant that documents in one format could not be read or accessed by computers or systems with a different operating system. Consequently, documents were usually shared manually, using paper. That all was changed when the Portable Document Format was introduced at the Windows OS|2 Conference in 1993. It was a solution born out of the vision that someday, technology would make it possible to eliminate paperwork from the office. 

Adobe had envisioned a versatile format that could be read by a universal program (Adobe Reader, or Acrobat Reader). As the technology developed, it was soon embraced by more and more users who realized its potential to streamline the document communication process. The PDF overcame all obstacles and became the standard for electronic documents today. 

When converting a physical document to an electronic document, the PDF is almost always the format of choice for the output. Although a PDF file is a versatile and flexible solution for moving documents from one computer or system to another, it has certain limitations. The primary issue with PDF files is that they capture documents in the form of an image, instead of structured data. This means that the data is inaccessible to computer programs and applications. This is not a small issue. All the data in a PDF invoice, for example, needs to be sent to an electronic accounting or ERP system. However, if that data is in a PDF format, the accounting system will be unable to recognize the data. 

As a result of this limitation, manual data entry has become the standard method for capturing the data in these PDF files and exporting that data to Excel spreadsheets or other formats that hold the data in a structured manner to be used by computer applications. The problem is that manual data entry is slow, inefficient, and expensive. The tedious task of copying out data into other applications has the potential to severely demotivate your team and is a terrible waste of their talent. 

Fortunately, there is a better way to get text from PDF files. Using an Intelligent Document Processing (IDP) platform, you can extract text from PDF online documents and instantly send the data to its proper destination. The best data extraction software will even include an “extract text from PDF to Excel” function so that you can quickly export the data to a format that’s compatible with your other systems. Utilizing an effective PDF-to-text converter can help you increase the efficiency of virtually every single document-based process in your business, from invoices to packing lists and everything in between. 

Extract text from PDF image

In order to extract text from PDF documents efficiently, a PDF-to-text OCR solution is required. OCR is short for optical character recognition and refers to the ability of a computer application to scan a document, identify the text characters within it, and then automatically extract that text as data that can be exported to various formats. There are two main kinds of OCR technology that both have the capability to extract text from PDF image scans. The first is called template-based OCR and relies on a series of rules and templates to be able to identify the fields and data types to extract for each document. 

This type of OCR has already been fairly widely used as a way to save time and costs on manual data entry. However, it is severely limited from a document management point of view. Although the technology can capture data very accurately from documents that have very little variation, its accuracy drops precipitously as the variation between documents increases. 

This means that template-based OCR works very well in situations where the documents all have a fixed, unchanging format. In the IRS, template-based OCR works well, because their paperwork is always consistent. However, each vendor is going to use a slightly different invoice. This requires businesses who implement template-based OCR to hire expensive experts to spend hours building new templates and writing new rules for every single vendor that they work with. 

A better solution than template-based OCR is AI-enabled OCR, also known as cognitive OCR. This character recognition technology uses deep learning to extract text from PDF documents. Cognitive OCR maintains itself instead of expensive experts, learning more about the fastest and most accurate ways of extracting data from your business documents as it goes. Rossum is an IDP solution with an AI-enabled OCR engine at its core. Our OCR engine possesses unique computer vision capabilities that enable the system to “skim” and “read” documents, much like a human would. 

This results in more accuracy and more speed, even when dealing with documents that have a high degree of variation. Whether your electronic documents are stored in a PDF file format or an image file format, a cognitive OCR solution is the best way to automate data extraction. 

Extract text from PDF programmatically

Manual data entry may not be such a bad way of extracting the text data from a PDF file if you only have to do it a few times. This method gives you the advantage of having an experienced professional be able to ensure that all the data is correct and makes sense. However, what if you need to run data extraction on hundreds of key business documents like invoices, receipts, work orders, and more? In that case, doing all that work manually doesn’t make sense. You need a way to extract text from PDF programmatically. 

One option for doing this is to build your own application. Although this may sound daunting, there are several tools that make it easier to do than you might think. It actually only takes a few lines of code to build a basic “extract text from PDF to Excel” Python program. The key is to use the open-source OCR engine, Tesseract. Tesseract is a library that is compatible with the Python programming language and can extract text from PDF files. However, you will need to find a library or program to connect this new tool to a user interface if you want your employees to be able to use it. Furthermore, the Tesseract library, though fairly robust, is not really suited to a professional business application. 

The ideal way to batch extract data from PDF to Excel spreadsheets is to utilize an IDP platform like Rossum. Rossum features an easy-to-use interface and a powerful queuing system that can take documents from a variety of sources and perform data capture on all of them in just a few clicks. The practical operation of this process is simple. 

All you have to do is upload your documents (from one channel or many) to the queue. Then, just check the boxes that describe the fields of data you want to capture. After that, a click or two for validation, and you’ll have all your data exported in the format of your choice. Our validation screen has been specifically designed to make it easier on your team and can automatically spot the areas that should be reviewed for accuracy. The best part about this is that whether you do it on one document or hundreds, the whole process will still only take seconds. 

Copy text from image

It’s fascinating to see how far technology has come. It is even more intriguing to consider the heights it could reach in the future. The PDF is now a commonplace standard that is almost fundamental to the world of business technology. Yet, just over two decades ago, we had no such standard for document formatting at all. The versatility of the PDF format was a massive breakthrough in its day and we continue to feel the benefits today. 

Although it was integral to facilitating the sharing of documents between professionals, the PDF did not solve the problem of manual data entry. Data still had to be copied out by hand from PDF files into other systems. Then, template-based OCR was developed and the document management space took a huge leap forward. For the first time, up to 50% of data entry tasks could be automated.

However, the hefty costs of maintaining and updating such a system began to be so expensive that costs were nearly comparable with manual data entry. Finally, cognitive OCR technology has been born that has the ability to copy text from image files regardless of the amount of variability there is between documents. 

The full power of document management automation can be realized with a platform like Rossum. With Rossum, not only can you copy text from PDF files and export it into a number of different formats, but you can also build powerful integrations. Instead of manually taking the exported data from Rossum and then importing it into your ERP or accounting systems, Rossum provides a versatile API that allows you to build your own integrations. These integrations can serve as software bridges that can automatically send the extracted data to its correct destination. In this manner, you can revolutionize your core processes and create completely touchless workflows. 

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Get text from structured & unstructured PDF documents without configuring rules or templates. Because every company deserves an automated data extraction process.