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As we enter the sixth decade of the information age, data has become a currency of the business world. However, it is estimated that a vast majority of a company's data remains unstructured, taking the form of written text found in various forms such as reports, contracts, and emails.

The manual process of collating this information requires a significant amount of time and resources, ultimately underutilizing or burdening a company's most valuable asset - its human talent.

Intelligent document processing is increasingly being used in various industries such as finance, healthcare, and government, to automate many document-intensive tasks such as invoice processing, contract management, and compliance reporting among others.

IDP is also being used to extract insights from unstructured data in many documents, thereby adding to the strategic value of business operations.

According to Straits Research, the worldwide market for intelligent document processing was valued at more than $ 1 billion in 2021 and is expected to reach more than $ 6 billion by 2027.

What is intelligent document processing?

Intelligent document processing (IDP) refers to the automation of data extraction from unstructured documents. It eliminates the need for manual data entry, reduces errors, and increases efficiency in document management.

IDP or intelligent document processing is a software that automates the process of extracting, processing, and analyzing crucial document data for business operations. Such solutions are key to modernizing and streamlining the often outdated, manual, and slow processes associated with document processing.

The "intelligence" in intelligent document processing comes from the use of Artificial Intelligence (AI) tools for data extraction. AI has the ability to process repetitive tasks without the cognitive limitations of humans; in fact, AI can produce more accurate results as it continues to process and learn.

How does IDP work?

An illustration of the IDP workflow

Intelligent document processing (IDP) typically involves a combination of optical character recognition (OCR), machine learning (ML), and natural language processing (NLP) techniques to extract structured data from unstructured documents.

Here's a general overview of how IDP technology works:

  • OCR is used to recognize and extract text from images or scanned documents, converting them into machine-readable text.
  • The extracted text is then processed using NLP techniques to identify and extract relevant data such as names, addresses, dates, and numbers.
  • Machine Learning algorithms are trained on a large dataset of labeled documents to recognize and extract specific information/fields from invoices, forms, or contracts.
  • The structured data is then validated and cleaned, and any missing or incorrect data is corrected or flagged for manual review.
  • The final output is a structured data format that can be easily integrated into other systems, such as databases or business intelligence tools, for further analysis and reporting.

IDP technology can learn and adapt to the specific requirements of different types of documents and industries, which makes it flexible and versatile. Intelligent document processing also allows handling large volumes of unstructured data, making it an efficient solution for automating data-intensive tasks such as invoice processing, contract management, and compliance reporting.


Automated document processing and intelligent document processing are related technologies but have distinct differences.

Automated document processing is used to convert paper documents into digital format, enabling them to be indexed and searchable in a database.

On the other hand, intelligent document processing not only digitizes and indexes paper documents but also extracts valuable information and provides insights from the data, taking document processing to the next level.

Here are some key differences between the two:

  • Intelligent document processing uses advanced technologies such as machine learning and natural language processing, whereas automated document processing relies primarily on optical character recognition technology.
  • Intelligent document processing is more sophisticated in its ability to understand complex/unstructured data, while automated document processing is more adept at plain old character recognition.
  • Intelligent document processing can leverage AI & ML to learn and adapt to specific data extraction requirements and can produce more accurate results as it continues to process and learn. This isn't possible with automated document processing!

Benefits of intelligent document processing

The benefits of IDP are numerous and far-reaching, and businesses of all types and sizes are quickly realizing the value of this technology in streamlining their operations and improving their bottom line.

Here are some of the key benefits of intelligent document processing:

Increased Efficiency

Intelligent document processing eliminates the need for manual data entry, thus increasing the efficiency of business operations. This can lead to faster processing times, which can be especially beneficial for businesses that deal with high volumes of unstructured data.

Improved Accuracy

According to research, the probability of human error when manually entering data into simple spreadsheets is between 18% and 40%. In complex spreadsheets, that probability increases to 100%. IDP solutions are at least 95% accurate, and can eliminate serious errors associated with manual document processing.

Cost savings

By automating repetitive and time-consuming tasks, intelligent document processing can significantly reduce labor costs. Additionally, IDP can help to reduce costs associated with errors and inaccuracies.

Better Decision Making

Intelligent document processing allows for the easy extraction of insights from unstructured data, making the process of decision making easier and more accurate. This can be especially beneficial for businesses that need to make data-driven decisions, such as finance, healthcare, and government.


Intelligent document processing can easily integrate with other systems, such as databases or business intelligence tools, for further analysis and reporting. This allows businesses to easily access and use the data that has been extracted, without having to manually feed it into another system.

Increase employee productivity

Intelligent document processing can improve both employee experience by eliminating the need for manual corrections, leading to faster approvals and reducing processing times. It also increases operational productivity by allowing valuable human resources to focus on more cognitive tasks instead of manual corrections.

Intelligent document processing use cases

The use of intelligent document processing is not limited to a specific sector, it can be applied to various industries, and it can be used to automate many different types of tasks.

By automating data extraction tasks, processes can be expedited, both on an objective task-performance time scale as well as through the avoidance of errors that are commonly associated with manual data extraction processes.

The above applications of IDP make it a versatile and valuable technology for businesses of all types and sizes. Here are some examples of how different teams or organisations leverage intelligent document processing:

  • Finance teams automate accounting, book keeping, loan processing, underwriting and accounts payable workflows among others.
  • Healthcare organisations draw valuable insights from medical records, prescriptions, insurance claims, lab results, patient information forms etc.
  • Insurance firms verify and analyse data from KYC documents, email attachments, transcripts, scanned agreements to process claims 80% faster.
  • HR personnel improve candidate processing speeds by pulling contact information, education, work experience, skills and qualifications from CVs and importing the same into an ATS.
  • Government agencies archive and verify government documents, tax returns, licenses, passports, permits and more.
  • Retail and logistics firms automate procurement, supply chain, inventory management and logistics workflows that involve multiple documents such as invoices, receipts, bills of lading, packing slips etc.
  • Law firms pull  or archive information from complex contracts, agreements, regulatory filings and court orders.
  • Real estate firms pull data from property titles, purchase agreements, lease agreements etc. into other business software.

How to choose the right IDP solution for your business?

When choosing an intelligent document processing solution, it is important to consider several factors to ensure that the solution meets the specific needs of your organization.

  1. To select an IDP that caters best to your organizational needs, the initial step is identifying your data processing requirements.
    • In what format is the data received or stored (email, scanned document, physical paper etc.)?
    • Is the data structured or unstructured?
    • What is the volume of data you receive, and at what frequency, and how much of it do you really need to automate?
  1. After identifying your organization's initial data processing needs, the next step is to assess which data sets would be most appropriate for intelligent document processing. Documents that require the most amount of time to process manually are ideal for IDP.
  1. After identifying the datasets that would benefit most from intelligent document processing workflows, the next step is to select the IDP software. Here are a few key points to keep in mind while comparing intelligent document processing software:
    • What is the expected accuracy level vs manual error rates? And can it be improved?
    • Is the underlying IDP technology template-based or can it handle complex data formats that don't follow any prescribed structure?
    • Can the IDP software read and understand all the types of data and documents that you currently deal with?
    • Does the software readily integrate with your business tools of choice? If not, can that feature be customised for your use case?
    • Can it handle your expected volume of data? And can it be scaled further?
    • How long will the setup take? And what level of support can be expected?
    • And finally compare competing quotes to get a better idea on pricing.

Nanonets for your IDP workflows

Nanonets is an intelligent document processing software that uses machine learning to automate all kinds of data extraction/processing workflows.

It utilizes a combination of OCR and deep learning algorithms to accurately extract data from various types of documents, such as invoices, receipts, bank statements, contracts and more.

Nanonets Intro

The user can train the Nanonets model by providing it with sample documents and the corresponding data that should be extracted from them. Once the model is trained, it can then be used to automatically extract data from new documents with high accuracy. Additionally, Nanonets also provides a user-friendly interface to help users to review and correct any errors in the extracted data.

  • OCR: Nanonets uses advanced OCR technology to accurately recognize text, numbers, and other characters from documents, including handwriting and machine-printed text.
  • Deep Learning: Nanonets utilizes deep learning algorithms to understand the context of the data and extract it accurately, even from complex and unstructured documents.
  • Customizable: Nanonets allows users to train their own models by providing sample documents and the corresponding data that should be extracted from them. The user can also customize the model by adjusting the extraction rules.
  • User-friendly Interface: Nanonets provides a user-friendly interface that allows users to easily review and correct any errors in the extracted data. Users can also export the extracted data in various formats, such as CSV, JSON, and Excel.
  • Multi-Language Support: Nanonets supports multiple languages, which allows users to extract data from documents written in different languages.
  • API Integration: Nanonets provides an API that allows users to integrate the IDP solution with other tools and systems, such as accounting software, enterprise resource planning (ERP) systems, and customer relationship management (CRM) platforms.
  • Scalability: Nanonets is a scalable solution that can handle large volumes of documents and data, making it suitable for businesses of all sizes.

Nanonets offers several advantages as an IDP solution, such as its ability to handle a wide range of document types, its high level of accuracy, and its ease of use. With Nanonets, users can quickly and easily extract data from documents, which can save them a significant amount of time and effort.


Businesses that can effectively utilize cutting-edge technologies like IDP will have  significant advantages in terms of efficiency and effectiveness. These technologies have the power to automate processes, reduce errors and increase efficiency. It's important to keep in mind that AI-based automation platforms are not magic solutions, they are the outcome of careful planning and collaboration between experts to solve real-world problems.

With the growing demand for automation and the increasing importance of data, IDP technology is poised to play a vital role in shaping the future of business. The time to invest in IDP is now, for those who do will be the ones who reap the benefits in the long run.