As we move to a digital future, businesses frequently process written, scanned, or digitally created documents such as invoices, checks, order forms, and bank statements. Traditionally a manual process, data extraction (capturing specific pieces of information from documents) will never become irrelevant. The data extraction market is expected to grow to $4.9 billion in 2027. And Gartner predicts 70% of organizations in 2025 will focus on innovative techniques to extract value from unstructured sources. However, the method by which businesses extract data has evolved—and there’s a new change that can simplify life for your company.
Manual data extraction has long been time-consuming. But new artificial intelligence (AI)-driven intelligent document data extraction solutions can help automate, reduce costs, improve accuracy and process documents at scale. It also allows employees to focus on strategic activities instead of trivial tasks like copying invoice numbers.
Let’s learn more about what data extraction can do for your business.
What Is Intelligent Document Data Extraction and Why Is It Necessary?
Document data extraction is the structured extraction of useful content from a larger text. Modern technology uses cognitive data capture to process documents rather than expending human labor on the efforts. Acting like a human brain, the AI enabled software works through documents with high speed and accuracy. It scans for the relevant pieces of data, then captures them for processing.
For example, suppose the document in question is a lengthy invoice. You might want to extract the buyer’s name, the seller’s name, the payment amount, and other data for entry into an ERP system. This extraction and ingestion can be completely automated thanks to intelligent document data extraction. It can also impact downstream activities such as metadata enhancement, payment reviews, and approvals. You can also combine the extracted information with other internal and public data sources to increase its value and actionability.
This technique of AI-based document extraction is already saving businesses time and money while increasing accuracy. However, just 28% of decision-makers focus on this application of artificial intelligence. Is it time you consider the use of this technology for your business? Read on.
Popular Applications of Intelligent Document Data Extraction
There’s a range of common applications for intelligent document data extraction. —and you can also develop your own. Let’s discuss a few of the popular use cases.
Improve Document Management and Governance
Traditional document management systems help organize and manage documents based on file metadata alone. Metadata contains information about the document, such as creation date, modified date, author, location, and file type. However, the basic file metadata doesn’t provide insight into the content of the documents. This information is often critical for better organization, classification, and governance of documents.
Intelligent data extraction can help. It pulls specific data fields of interest and enriches the metadata by adding context and content. As a result, document management can be aligned with the business requirements better.
For instance, you might automatically extract the “Invoice date,” “Invoice number,” and “Product ID” information from each invoice, adding it to specific metadata fields. This can help employees quickly find relevant invoice documents based on the additional parameters and process them efficiently without browsing through the entire document repository.
Such enriched metadata can also help enforce data access, retention, privacy, and other governance policies at scale. This helps organizations comply with internal and external policies and regulations. Intelligent data extraction can also help identify sensitive information present in the document and classify it for further processes such as labeling, redaction, or document review.
Overall, intelligent data extraction can help improve document management, data governance, data quality, usability and discoverability.
Intelligent Content-Based Search
A content-based search works by looking for what the user wants within each resource in addition to the metadata. However, while such a search is a step up from file metadata-based searches, it’s seldom efficient because the search doesn’t include context. For example, a search for a document containing a unique invoice number like “10001” could return hundreds or even thousands of documents if that number was also used as a supplier ID or a payment amount.
AI-based document extraction can uniquely identify information contained within a document along with context. This makes the content-based search much more intelligent, relevant, and powerful. Imagine searching by an invoice number and receiving the exact document you need, even though thousands of other documents might have included a similar number in some other context.
The extracted fields also let people filter their searches more effectively, as intelligent content-based search lets you produce queries as complex as you want. For instance, you can search exclusively among invoices from the past two months for a given amount. Choose whatever parameters you want. The discovery of documents becomes faster, more relevant, and more efficient, increasing employee and process productivity. In fact, a PwC study noted 40% fewer hours are needed to process routine paperwork when even the most rudimentary AI-based extraction techniques are implemented.
Intelligent content search also reduces document loss or misplacement—a costly problem. Lost or misplaced documents can wreck sales and customer relationships while exposing your organization to the risks of regulatory non-compliance.
Automate Processes With Data Extraction
Document data extraction sets the groundwork for automating countless slow, expensive, and error-prone manual processes. For example, a large manufacturing company can automate accounts payable or accounts receivable.
Manufacturing companies tend to have thousands of suppliers and purchasers. They may deal with as many as 10,000 invoices or remittances per month—besides other purchase documents from vendors, such as order forms. Traditionally, the business may have a team looking at each document and manually capture, verify, and enter the details into an enterprise resource planning (ERP) system for processing. Such an approach is often time-consuming, resource-intensive, and error-prone.
Intelligent data extraction can automate this manual process. This enables businesses to process thousands of documents each day with the help of a significantly smaller team, resulting in greater efficiencies and improving accuracy multifold.
Other popularly cited examples are employee onboarding, Document and ID verification, and release processes.
Automate Document Data Extraction With Solix
Document data extraction is an essential process for many businesses. However, it also eats up valuable human labor hours—at least until now.
SOLIXCloud ECS offers cloud-based secure file storage with intelligent content services such as information governance, file sharing and collaboration, and intelligent document data extraction. Solix AI-enabled data extraction technology offers a way to simplify and streamline data extraction across a range of document types including invoice documents, remittances and more. This helps you organize documents more effectively, power content-based search, enable granular data governance, and further automate business activities. It can be the key to digitally transforming your business for the modern era.