Beginner’s Guide to Intelligent Document Processing (IDP): All You Need to Know.

Data is essential to every workflow process since it facilitates business growth, improves operational effectiveness and efficiency, and eventually boosts revenue. In today’s enterprises, there is an abundance of data, making it challenging to separate out important information from unimportant noise. Traditional document capture technologies cannot meet the needs of today’s digital environment for document processing. Large volumes of unstructured data may be processed more quickly thanks to automation of document processing. Workers’ labor-intensive, error-prone manual work is eliminated, resulting in time savings and increased efficiency. This enables businesses to take advantage of new opportunities rapidly without having to hire more personnel, enhance compliance transparency, enrich automated workflows with useful insights, and accelerate ROI. Let’s learn more about this.

What is Intelligent Document Processing (IDP)?

According to Allied Market Research, the intelligent document processing market, sized at around $1Bn, is projected to grow more than 20 percent CAGR to surpass $7Bn by 2030. Businesses are able to automate document processing thanks to its rapid advancements with artificial intelligence (AI) at its core. IDP classifies documents, extracts information, and verifies data using automation powered by AI and supported by machine learning (ML). Through automation and the structuring of unstructured data, it further automates and accelerates the processing of documents.  IDP may also use tools for robotic process automation (RPA) and natural language processing (NLP) to expedite and reduce the likelihood of errors in the conversion from analog to digital.

How does IDP work?

Beginning with intelligent document recognition, IDP scans and categorizes documents using sophisticated deep-learning AI technology. IDP technology is capable of learning up to 190 languages and can read and comprehend documents similarly to a data processing worker. After the data has been categorized, intelligent document automation software starts to extract the information that is important to your company. Through the use of cognitive AI technologies that isolate particular data points from the broader document, extraction is made possible. A business process management approach that includes intelligent document processing is one that is worth considering if your organization has an enormous amount of organized, semi-structured, or unstructured data.

What are the key stages of the IDP workflow?

  • Document gathering

Gathering various sorts of paper or electronic documents from various content sources is referred to as document collection. The integration of IDP solutions with hardware, like scanners, allows for the digitization of paper and handwritten documents while also accelerating the scanning process. Through built-in integrations, documents presented in digital formats, such as PDF, Word, and Excel files, emails, etc., are also ingested.

  • Document classification

This stage seeks to categorize documents according to their kind, content, or structure. The process also includes figuring out where the document starts and ends. It is possible to classify documents using AI. In the case of scans or document images, based on image patterns with the aid of computer vision algorithms; and based on the textual content, using NLP techniques — in the case of electronic documents. The subsequent extraction procedure is substantially improved by document categorization since the data from a given document is delivered to the appropriate workflow more quickly.

  • Data extraction

Businesses can take the right first step toward building an enhanced document processing strategy thanks to intelligent data extraction. It is also a must for creating a successful automation process for your entire firm. Data is gathered and examined by intelligent capture utilizing a variety of toolkits in order to extract crucial information and send it to lead systems. Additionally, machine learning makes it possible for intelligent data capture software to train itself to distinguish between various data kinds and effectively classify common and uncommon data, accelerating and improving the process over time.

  • Data validation

In the context of IDP, data validation is a vital stage since it assures that businesses can entirely trust the data. Data validation requirements are determined by particular business demands. By offering cross-checking and verification capabilities, the majority of the acquired data may be validated automatically. When the level of data recognition falls below the predetermined threshold, data validation via human in loop is typically used. Data validation is a preventative measure to protect one of the most important assets.

  • Data integration

Conventional document capture methods extract data and input it into content management programs without providing insights. However, contemporary IDP software connects with numerous downstream systems such as ERPs and workflows, where it may support businesses in making wise decisions.

  • Data analytics

By dissecting the information and even the document processes into individual component elements, this technique analyzes data on documents. Then, in order to provide a deeper understanding of their contents and associated document processing workflows, an AI model examines the links between parts and assesses how they are interrelated.

  • Workflow integration

The information is exported to internal data systems and other business process workflows are integrated as the last step of IDP. The information is instantly accessible to other departments after it is published to your internal data systems, freeing up your entire organization to concentrate on taking prompt action and offering clients efficient service. To add AI/cognitive capabilities to RPA activities, intelligent document processing might then be coupled with RPA systems as a sub-process.

Now that we are aware of the stages of IDP workflow in an enterprise, in the section below, let’s look at some of the main benefits of IDP and reasons why you should consider deploying IDP at your company.

  1. Increases effectiveness and efficiency 

The fact that these tools lessen the need for human intervention and labor-intensive tasks in many document-centric workflows is one of the primary advantages of intelligent document processing. In actuality, extracting, converting, sorting, and indexing data just takes a few seconds using these IDP solutions. Unstructured documents are also included in this. This could significantly improve the efficiency of these crucial corporate operations. Additionally, the degree of automation that IDP solutions provide improves the general effectiveness of the daily processes in many companies.

  1. Reduces error 

Businesses can process papers effectively and with fewer mistakes thanks to it. By lowering the possibility of data entry errors, such a platform can increase productivity and reduce the difficulty of tasks. As a result, businesses may better serve their clients and guarantee ongoing consumer satisfaction.   

  1. Enhances customer experience

The ability to respond to consumers more quickly and offer higher service comes with enhanced speed and efficiency. The regular inundation of emails that clog inboxes is a major area for automation. According to a study of 1,000 businesses, the majority of consumer emails are either ignored or receive responses that take more than 12 hours on average. However, most clients anticipate a response in one to four hours. Businesses that use AI and document automation can outperform expectations and increase sales as a result.

  1. Simplifies compliance

By extracting data from documents and categorizing them in accordance with predetermined criteria, it can assist firms in automating and streamlining their compliance operations. By doing so, you can ensure that compliance-related data is regularly and accurately recorded while also cutting down on the time and expense involved with manual data entry and document review. Furthermore, an IDP solution can assist in the development of a searchable database of compliance-related data that may be utilized for auditing or other functions.

  1. Lowers operating expenses 

To cut down on labor and overhead costs, IDP automates document handling and allows for time and resource savings both during periods of stable operations and during periods of noticeable workload increases, such as seasonal surges.   

  1. Provides scalability

The IDP solution is process independent and suitable for a wide range of applications. It functions as a platform for the scanning and processing of many document formats, sizes, and sources, including images, faxes, and excel sheets. IDP is very scalable and efficient for any organization thanks to all these advantages.


Businesses can successfully use cutting-edge IDP technologies to benefit greatly in terms of efficacy and efficiency. It’s important to note that AI-based automation platforms are the result of meticulous design and professional collaboration to address real-world data processing concerns. WNS-Vuram’s Intelligent Document Processing capabilities have the ability to automate processes, lower error rates, and boost productivity, and can play a significant role in influencing the direction of businesses given the rising demand for automation and the importance of data. Now is the ideal time to make an investment in IDP, as those who do so will ultimately witness tremendous benefits. Talk to our experts today or write to for an expert consultation.

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