In recent years, artificial intelligence has brought a wave of change in the way companies do business. AI has given rise to several new and robust technologies in different fields, including automation and data extraction.
In this article, we will explore how AI is being used to extract data from PDFs, the benefits of this cutting-edge technology, and some of the best tools and techniques available on the market for PDF data extraction with AI.
“98% of companies are accelerating AI to increase automation and solve labor market challenges.” - PwC’s annual AI business survey, 2022
Challenges of manual data extraction
PDF documents are ubiquitous in the digital age, and they contain a wealth of information that can be of great value to individuals and organizations alike.
However, extracting text from PDF files manually can be a time-consuming and error-prone process, particularly when dealing with large volumes of documents.
The complexity of PDF files makes it more challenging to extract table data which could lead to inaccuracies.
Fortunately, artificial intelligence has made significant strides in recent years, and it is now possible to use machine learning algorithms to automate the extraction of data from PDF files.
Benefits of PDF data extraction with AI
AI OCR optical character recognition has undoubtedly brought many advantages to companies. Powered by ML algorithms, we can safely say that data accuracy has incredibly improved.
More accurate data
AI-powered data capture eliminates the need for manual data entry and hence, reduces human errors. Data extraction is done with a high level of accuracy.
By automating the PDF data extraction process, organizations can significantly reduce the time and effort required to process large volumes of PDF files. This, in turn, can increase productivity and free up staff to focus on other important tasks.
Ability to handle large volumes of PDFs
AI-powered PDF data extraction tools are capable of handling large volumes of PDF files, making it possible to extract data from thousands or even millions of documents in a fraction of the time it would take using manual methods.
This can be particularly useful for organizations that deal with large amounts of data on a regular basis, such as financial institutions, healthcare providers, and food delivery companies.
Extract data from unstructured documents
AI can easily parse data from documents with different layouts and formats and convert unstructured data to structured data.
How does data extraction with AI work?
AI OCR is combined with ML and NLP, making it possible to scan and read documents in different languages within seconds.
- Preprocessing: Documents are first preprocessed to prepare them for data extraction, for example, converting them into plain text.
- Text recognition: OCR is one of the oldest tools used to analyze images, handwritten text or scanned documents so that they are machine readable.
- Data extraction: The AI system processes the documents by identifying keywords, metadata, fields and patterns and proceeds to data extraction.
- Data validation: Sometimes, the data needs to be reviewed manually to ensure that it meets specific criteria.
Use cases of automated data extraction with AI
Data is the backbone of every industry that powers every data-driven decision from profit calculations to acquiring new customers.
Invoicing and billing
Many organizations receive large volumes of invoices and bills in PDF format. Every supplier’s invoice has its own format and sometimes the procurement agent may change or the invoice itself may have some typos.
Using AI-powered software, companies can process invoices quickly and accurately. This can help streamline the billing process and improve cash flow management.
Financial statements and audit reports
Every year, firms have to prepare their financial audits which include analyzing large volumes of transactions, clients’ data, and account balances. Those data are usually stored in PDF files and can go up to thousands of pages.
By implementing an AI solution, companies can save thousands of manual hours.
Healthcare providers and research institutions must analyze large volumes of medical records and research papers in PDF format. AI-based document processing tools.) can be used to extract relevant data such as patient information, medical conditions, and research findings. This can help improve healthcare outcomes and advance medical research.
Best AI tools for PDF data extraction
When choosing an AI tool for PDF data extraction, it's important to consider factors such as the complexity of the data to be extracted, the volume of PDF files to be processed, and the level of customization and integration required.
We’ve gathered some of the top PDF parsers integrated with AI below.
Parseur for template-based extraction
Parseur has a strong PDF parsing engine and is the first data extraction tool with an AI OCR, Zonal OCR, and Dynamic OCR.
Parseur provides AI-assisted templates and ready-made fields to ease the data extraction process from PDFs. There are no coding or parsing rules involved. The platform is point-and-click and is integrated with 1000+ applications.
Google Cloud document AI
Google Cloud Document AI is a cloud-based service that uses OCR and NLP (natural language processing) algorithms to extract text and data from scanned documents, including PDF files. It can extract metadata such as dates, names, and addresses, and output the data in a structured format.
Mindee is a document parsing API that offers customized AI solutions to businesses. It is more suitable for developers helping them to automate different workflows.
The future of AI OCR
AI PDF extractors have had a significant impact on businesses all around the world. More companies are adopting AI technologies to automate their repetitive tasks. If they want to stay competitive in today’s AI world, then incorporating those tools into their business strategies is a must.