Intelligent Document Processing (IDP) is a type of automation technology that is designed to extract relevant information from unstructured documents such as invoices, receipts, contracts, and forms. This technology combines machine learning, artificial intelligence, and natural language processing to extract data, understand the content, and automate workflows.
In this article, we will discuss the key components of intelligent document processing, how it works, and the benefits of using
What is intelligent document processing?
Intelligent Document Processing (IDP) is a type of automation technology that uses machine learning, artificial intelligence (AI), and natural language processing (NLP) to extract data from unstructured documents, such as invoices, contracts, and forms. The technology enables organizations to automate the process of document processing, which has traditionally been a time-consuming and error-prone manual task.
IDP is designed to handle a wide range of document types and formats, including scanned images, PDFs, and emails. The technology is capable of recognizing text characters, identifying key data points, and extracting information with a high degree of accuracy. This makes IDP a valuable tool for organizations that handle large volumes of documents and need to extract data quickly and efficiently.
Components of IDP
As noted above, there are three main components of IDP. Let’s explore each one of them in more detail.
Optical Character Recognition (OCR)
OCR is a technology that enables machines to recognize printed or handwritten text characters from scanned documents. OCR technology has come a long way in recent years, and it is now able to recognize a wide range of fonts and characters with high accuracy.
Natural Language Processing (NLP)
NLP is a type of artificial intelligence technology that enables machines to understand human language. With NLP, machines can analyze the text in documents and extract the relevant information based on the context.
Machine Learning (ML)
Machine learning is a subset of artificial intelligence that involves training machines to learn from data. In the context of IDP, ML algorithms are used to train machines to recognize patterns in unstructured documents and extract the relevant information.
How IDP works
IDP technology typically follows a process that involves the following steps:
- Document ingestion -The first step in IDP involves ingesting the unstructured document into the system. This can be done in several ways, including manual uploading, email, or via APIs.
- Document classification – Once the document is ingested into the system, the next step is to classify the document based on its type. For example, if the document is an invoice, the system will classify it as such.
- Data extraction – After the document is classified, the system uses OCR technology to extract the text from the document. The extracted text is then analyzed using NLP to identify the relevant data points, such as the invoice number, date, and total amount.
- Validation and verification – Once the relevant data points have been extracted, the system validates and verifies the data to ensure its accuracy. For example, the system may compare the invoice number with the vendor’s database to ensure that it is valid.
- Data integration – After the data has been validated and verified, it is integrated into the appropriate system or application. For example, if the document is an invoice, the data may be integrated into an accounting software application.
Benefits of intelligent document processing
IDP offers several benefits to organizations, including increased efficiency, improved accuracy, cost savings, enhanced compliance, and scalability. By automating the process of document processing, IDP reduces the time and effort required to extract data from unstructured documents, resulting in increased efficiency.
The technology also offers improved accuracy compared to manual data extraction, which reduces errors and can result in cost savings. IDP can help organizations comply with regulations and standards by ensuring that data is accurate and consistent across systems. Finally, IDP can scale to handle large volumes of documents, making it ideal for organizations with high document processing needs.
Let’s sum up some of the key benefits of using IDP technology, including the following:
- Increased efficiency – IDP technology automates the process of document processing, reducing the time and effort required to extract data from unstructured documents.
- Improved accuracy – IDP technology uses machine learning algorithms to extract data, resulting in increased accuracy compared to manual data extraction.
- Cost savings – By automating the process of document processing, IDP technology reduces the cost of manual labor and eliminates errors that can result in costly mistakes.
- Enhanced compliance – IDP technology can help organizations comply with regulations and standards by ensuring that data is accurate and consistent across systems.
- Scalability – IDP technology can scale to handle large volumes of documents, making it ideal for organizations with high document processing needs.
Intelligent Document Processing (IDP) is a powerful automation technology that enables organizations to extract relevant information from unstructured documents quickly and accurately. By combining OCR, NLP, and ML technologies, IDP can automate the document processing process, resulting in increased efficiency, improved accuracy, cost savings, enhanced compliance, and scalability.
As more organizations adopt IDP technology, we can expect to see significant improvements in document processing workflows and overall business efficiency.