Portable Document Format (PDFs) is the most common file format in which most of the files are saved. Be it a word document, an excel sheet or a PowerPoint presentation, all of them are convertible to PDFs. When a word, excel or a presentation has to be shared via an email or any other messaging channel such as WhatsApp or Facebook Messenger to any other person, it is highly recommended that the file is converted to a PDF as it helps in retaining the structure and orientation of the data in the file.
A scanned document is also usually saved in PDF format. This could be print-text scanned documents like a passport, driver’s license or an identity card or it could handwritten documents as well. Mostly for legal and compliance purposes, even the photocopies of such documents are converted into PDFs.
However, at times the data from a PDF document has to be extracted in some other format for a variety of purposes. Multiple documents that are saved in PDF format may also have time-sensitive data that needs to be discovered as quickly as possible. This is not possible when there are numerous documents saved in PDF format and therefore, the need for data extraction from it. Another reason to extract data from PDF files could be to store the data on the cloud or on certain software to ensure that the data can be quickly and easily discovered.
Extraction of data from PDF becomes a difficult task in the case of handwritten notes. Since alphabets and characters written by pen or pencil are quite hard to detect, extraction of data from a handwritten scanned PDF file is not an easy job. Thanks to Artificial Intelligence and Deep learning technologies, data from handwritten files that are saved as PDFs can now be extracted with higher accuracy.
Use Cases of PDF Data Extraction
Invoices & Receipts
Organisations partner up with various other vendors and receive invoices and receipts from them. At times, these invoices or receipts are sent as PDF. Invoices and receipts act as proof of order and money sent to these vendors. Problem is that since there is no universal standard for an invoice and therefore, extracting data manually becomes difficult.
If you are a banking organisation, a real estate company or any other firm that has to deal with a lot of legal and compliance-related documents, you have to deal with PDFs on daily basis. Files such as address proof, electricity bill, property documents, and so on are also sent and received via email usually in PDF formats so that the file does not get distorted. But if the data from it has to be saved on some other application, the data has to be extracted from it.
Many organisations require various types of identity proofs such as passport copy, driver’s license or a national identity card. These are too usually sent in PDF format. For the organisation to save time and search individual details easily, it only makes sense to extract data from these various files and consolidate it in one format on one application and therefore the data from PDF is extracted.
Process of Extracting Data from PDF
So far, we have understood why the files are saved in PDF in the first place and why the data from PDF is extracted. Now we will understand how do KlearStack’s solutions help to extract data from PDF.
KlearStack uses Artificial Intelligence and Machine learning technologies with Optical Character Recognition (OCR) to extract and interpret data accurately. Be it a printed text file or a handwritten one, KlearStack’s solution can help with the extraction of any and all kind of data.
Through OCR, the data in the PDF is scanned and identified as to which field does it exactly belongs to. The field name and its corresponding data are matched and extracted from it. For example, a passport has a name, passport number, date of birth, date of issue, date of expiry and nationality as some basic fields.
Data from these fields will be scanned, identified and matched if there are several passport copies, irrespective of which country’s passport it is. So if one country’s passport template/ structure is different from another, it does not matter as the data from the field names are extracted and matched.
Bulk Data Extraction is therefore quite easily achievable. The process remains more or less the same. Data is converted from a variety of PDF documents that have different templates into a uniform and standardized data schema. This helps PDF files to be organised and structured. Instead of going through various PDF files and looking for a specific dataset, you can easily it on the platform you have extracted the data to.
Apart from printed text and handwritten, tables and images can be extracted as well. PDF’s may contain large sets of tables that have crucial information. Data from this can be easily captured and stored on the respective platforms.
PDF is the go-to document format for saving files in most cases. We have explored various reasons and use cases as to why an organisation would like to extract data from it and understood the process of how it works. Evolution in technology has helped us to achieve this today and KlearStack has capitalized on this technological evolution to make day-to-day activities of businesses seamless and efficient.
KlearStack’s solution helps you achieve this as well. With the deep learning and automation solutions kept in place, our solutions can help automate your entire documentation and data capture from start till the end. If you are interested to know more about our solutions or would like to schedule a call with our experts, click here.