The Definitive Guide to Intelligent Document Automation

Explore how Intelligent Document Automation can revolutionize data handling and accuracy across industries with AI and ML.

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Did you know that workers spend over 8 hours per week dealing with document-related problems? Intelligent Document Automation (IDA) is changing this narrative. 

By blending cutting-edge AI and machine learning, IDA is redefining how we handle documents – turning hours into minutes and chaos into order. 

This innovative approach is not just an upgrade; it's a complete overhaul of traditional document processing, offering unparalleled efficiency and accuracy.

What Exactly is IDA? 

IDA is a cutting-edge technology that uses advanced artificial intelligence (AI) and robotic process automation (RPA) to digitize and automate document-centric processes within an organization.

It combines natural language processing, machine learning, and cognitive computing to extract, classify, and process data from various documents, such as invoices, contracts, forms, and emails.

This technology aims to streamline and optimize document-intensive tasks by eliminating manual data entry, reducing errors, and improving overall efficiency. As a result, organizations can save time and resources, increase productivity, and enhance decision-making processes.

Brief History and Evolution

IDA has rapidly evolved over the past few decades, revolutionizing the way businesses handle their documents and data. This technology has its roots in the early 2000s, with the emergence of document management systems that allowed companies to digitize and store their documents electronically. 

This was a significant advancement from traditional paper-based document processing, but it lacked the capabilities to automatically extract, process, and analyze the data within those documents.

In the mid-2000s, the concept of Intelligent Document Automation began to take shape, as businesses increasingly sought ways to streamline their document-centric processes. 

At first, this involved the use of Optical Character Recognition (OCR) technology to scan and convert printed documents into digital text. While this was a significant step forward, the real breakthrough came with the integration of machine learning (ML) and AI algorithms into document automation platforms.

As AI and ML capabilities continued to advance, IDA solutions became increasingly sophisticated, enabling businesses to automate the extraction, validation, and processing of data from a wide variety of documents, including invoices, contracts, and forms. These solutions could also be trained to recognize and understand the context of the documents, making them more adaptable to complex and dynamic business processes.

Today, Intelligent Document Automation has become an integral part of business operations across industries, offering a wide range of benefits, including improved accuracy, efficiency, and compliance. Moreover, the evolution of cloud-based IDA platforms has made this technology more accessible and scalable for businesses of all sizes.

Importance of Intelligent Document Automation in the Digital Era

With businesses and organizations generating and managing an ever-increasing amount of data and documents, automating the processes of creating, managing, and analyzing documents is essential for staying competitive and efficient.

Time and Cost Savings

  • Intelligent document automation significantly reduces the time and costs associated with repetitive and time-consuming tasks like data entry and document processing.
  • Automation allows organizations to reallocate resources to more strategic and high-value activities.

Improved Accuracy and Compliance

  • Automation minimizes errors and inconsistencies in documents.
  • Leads to enhanced accuracy and better compliance with regulatory standards.

Enhanced Data Utilization and Decision-Making

  • Intelligent automation facilitates the extraction and analysis of data from documents.
  • Provides valuable insights into customer behavior, market trends, and business performance.
  • Aids in informed decision-making and strategic initiatives.

Improved Collaboration and Communication

  • Automates document workflows and approval processes.
  • Increases the efficiency and transparency of operations.
  • Results in faster decision-making, reduced bottlenecks, and improved overall productivity.

Core Components of Intelligent Document Automation

At the core of Intelligent Document Automation are several key components that work together to achieve its goals. These include:

1. Document Capture: IDA begins by capturing documents from various sources such as emails, scanned files, and digital forms. Advanced OCR technology is used to extract text and data from these documents, making them searchable and editable.

2. Data Extraction: Once the documents are captured, IDA uses advanced data extraction techniques to identify and extract specific data points from the documents. This could include customer names, addresses, invoice numbers, and more. Machine learning algorithms are utilized to continually improve the accuracy and efficiency of data extraction.

3. Document Classification: IDA classifies documents based on their content and purpose, allowing them to be routed to the appropriate workflows or stored in the right digital repositories. Through natural language processing (NLP), IDA is able to understand the context and meaning of documents, making it easier to categorize and manage them.

4. Workflow Automation: After capturing, extracting, and classifying the documents, IDA automates the workflow processes related to them. This could include routing documents to the right personnel for review and approval, triggering specific actions based on the content of the document, or integrating with other systems to initiate further processes.

5. Intelligent Document Management: Finally, IDA includes intelligent document management capabilities, allowing organizations to store, organize, and retrieve documents more efficiently. This includes version control, digital signature integration, and audit trails to ensure compliance and security.

Document Handling in Various Industries 

Intelligent Document Automation (IDA) has diverse applications across various industries, significantly enhancing efficiency and accuracy in document handling.


  • Automated Financial Document Processing: IDA streamlines the handling of a wide range of financial documents, such as loan applications, investment reports, and compliance documents. It automates data extraction, validation, and processing, significantly reducing manual effort.
  • Risk Reduction and Accuracy: By automating routine financial tasks, IDA minimizes human errors, enhances the accuracy of financial data, and helps in maintaining regulatory compliance, which is crucial in the finance sector.


  • Streamlined Claims Processing: In the insurance industry, IDA accelerates the processing of claims and policy documentation. It quickly extracts information from claims forms, assesses them against policy details, and automates approvals or rejections based on set criteria.
  • Improved Customer Service: By speeding up document processing, IDA enables insurance companies to respond to customer queries and claims more efficiently, leading to improved customer satisfaction and loyalty.


  • Efficient Patient Record Management: IDA is instrumental in managing patient records, including medical histories, treatment plans, and billing information. It ensures that records are updated promptly and accurately, enhancing the quality of patient care.
  • Regulatory Compliance and Billing: Healthcare providers use IDA to maintain compliance with various health regulations. It also automates billing processes, ensuring accurate and timely invoicing, and reducing the administrative burden on healthcare staff.

Case Studies of Successful Implementation has been instrumental in revolutionizing the way organizations handle their documents through Intelligent Document Automation. With Feathery, businesses have been able to streamline their document processing, reduce human error, and improve overall efficiency.

Case studies have demonstrated successful implementations of Feathery in various industries such as finance, healthcare, and legal. 

Here are a few examples:

  • Financial Services: A leading wealth advisory firm uses Feathery to analyze a client’s bank statements and investment reports to extract the stock holdings and balances. This extracted data is synced directly to their CRM (Salesforce) and wealth management system (eMoney) so that they can provide the client with personalized financial reporting and advice.
  • Insurance: A leading insurance brokerage uses Feathery’s OCR to analyze a user’s existing policy and documents to prefill key parts of the form, increasing conversion significantly. 
  • Manufacturing: A large manufacturing company uses Feathery’s OCR to extract order information from various Purchase Order  (PO) documents that they receive from clients to speed up their sales process

Ready to try Feathery?

Feathery is a highly customizable form and workflow builder, making it an ideal choice for devs and product teams.

Enter Feathery: The End-to-End Intelligent Document Automation Workflow Solution

Feathery offers a straightforward approach to document extraction and workflow management, simplifying the process of handling data from various documents. This tool is designed to automate the extraction of information from common documents like invoices, purchase orders, and receipts and fits well with existing systems to help improve workflow efficiency.

AI-Enabled Data Extraction

Feathery provides an AI-based data extraction feature that enables users to easily specify what data to extract from documents using everyday language. Additionally, it can format the data uniformly as needed.

For example, users can tell Feathery to extract stock holdings from financial statements, organize them by stock symbol and dollar amount, and display the stock symbol in uppercase. This tool can sort these results into designated fields and handle multiple entries for each field in cases with several stocks.

Flexible Data Extraction

Feathery enhances the way data is extracted from documents. It gives users the ability to specify exactly what data they need extracted, using simple, natural language commands.

For instance, you can direct Feathery to "collect all stock holdings, categorize them by stock symbol and the amount of each holding, and display the stock symbols in uppercase."

This method enables efficient organization of data into specific categories, like one for stock symbols and another for their respective dollar values.

Feathery's sophisticated extraction technology can accurately handle and organize multiple data entries for each specified field, demonstrating its versatility and accuracy.

User-Friendly Interface

Feathery's interface is designed for clarity and interaction, visually showing the data extraction process in action. It marks the areas of the document being processed by encircling them.

This visualization not only enhances the understanding of the process but also invites user interaction. If the system concentrates on a wrong document section, users can adjust the focus area themselves. Such interactions help Feathery learn and improve, enhancing its precision over time.

Seamless Integration with Document Storage Platforms

Feathery recognizes the varied needs of businesses and integrates smoothly with several document storage platforms like Google Drive, Dropbox, and Egnyte.

This feature makes it easier to access and manage documents for extraction and storage purposes, thereby streamlining the whole workflow process.

End-to-End Document Workflow 

Feathery offers more than just data extraction; it provides a full-fledged document workflow solution. Here's how Feathery can streamline your document-handling process:

Uploading Documents

Begin by integrating a simple form on your platform, allowing customers to upload documents like bank statements effortlessly. This user-friendly form serves as the starting point for an efficient and streamlined document collection process.

Automated Data Extraction

Upon the upload of a document, such as a bank statement, Feathery springs into action. It automatically extracts essential information like account balances, transaction histories, and other relevant financial details. This automated process significantly reduces manual effort and minimizes the likelihood of errors.

Optional Internal Review

For added accuracy, Feathery offers an optional internal review stage. Here, a designated team member can inspect the extracted data for precision. They have the option to approve or reject the data, providing an extra layer of verification and human insight into the automated workflow.

Data Integration and Distribution

The concluding phase involves the efficient distribution of processed data to various systems. Feathery's ability to integrate with over 100 different systems and platforms, including CRM tools like Salesforce and various underwriting systems, is a key feature. This integration is made effortless with user-friendly API connectors, ensuring seamless data transfer across your business tools.

Want to discover how Feathery can transform your document management process with its sophisticated OCR and AI-driven data extraction technology? Book a Demo to learn more. 

Integration with Existing and New Systems

Integrating with Existing IT Systems

Integrating intelligent document automation with existing IT systems is essential for streamlining processes and maximizing efficiency. The process involves several key steps, beginning with an assessment of the current IT infrastructure to identify potential integration points. 

Next, it's important to ensure that the intelligent document automation solution is compatible with the existing systems and can seamlessly communicate with other platforms and applications.

Once compatibility is confirmed, the integration process can proceed, which typically involves working closely with IT teams to develop and implement the necessary connections and APIs. This may also involve configuring the intelligent document automation solution to align with the data formats and protocols used by the existing IT systems.

Testing and validation are crucial stages to ensure that the integration is successful and that the intelligent document automation solution can effectively interact with the existing IT systems without disrupting operations. Ongoing monitoring and support are also important to address any issues and make adjustments as needed.

Compatibility with Various Digital Infrastructures

Intelligent Document Automation solutions are designed to be compatible with a wide range of digital infrastructures. These solutions are built to seamlessly integrate with different systems, such as customer relationship management (CRM) platforms, enterprise resource planning (ERP) systems, and content management systems (CMS).

Intelligent Document Automation software offers robust compatibility with various file formats, including PDF, Word, Excel, and more, allowing users to process and manage documents without the need for manual intervention. Additionally, these solutions can be easily accessed through web browsers and mobile devices, ensuring flexibility and accessibility for users across different digital platforms.

Feathery is an advanced data extraction platform that allows you to easily gather and extract data from various sources, including websites, PDFs, and more.

With Feathery's 100+ native integrations and no-code API connectors, you can seamlessly send the extracted data to any system, such as your underwriting system, Salesforce, and many others.

Future Trends and Developments

IDA will continue to advance with the integration of AI and ML algorithms. This will enable IDA systems to automatically extract, classify, and process unstructured data from various types of documents with higher accuracy and efficiency.

Furthermore, the development of NLP technology will allow IDA to understand and analyze the content of documents in a more sophisticated manner, facilitating better decision-making and automation of complex tasks.

Another future trend in IDA is the incorporation of blockchain technology for enhanced security and transparency in document management. This will ensure the integrity and authenticity of documents, reducing the risk of fraud and unauthorized access.

IDA systems will evolve to provide more customizable and user-friendly solutions, enabling businesses to tailor automation processes to their specific needs without requiring extensive programming knowledge.

The future of intelligent document automation will be characterized by more advanced AI capabilities, increased security measures, and greater flexibility and usability for businesses across various industries.

Key Takeaways

IDP solutions, exemplified by platforms like Feathery, are transforming the handling of large volumes of documents in industries such as healthcare, insurance, and finance. By integrating deep learning, these solutions convert diverse document formats into machine-readable formats, streamlining document intake, analysis, and reducing the reliance on manual processing. 

Feathery enhances this process by offering intuitive interfaces and efficient electronic document management, significantly improving process efficiency and customer experience. The application of IDP in document processing operations allows business users to focus on strategic roles, moving away from labor-intensive document management.

Frequently Asked Questions

What is Intelligent Document Processing?

Intelligent Document Processing refers to the use of AI, particularly deep learning, to automate the processing and analysis of large volumes of documents in various formats.

How does IDP improve customer experience?

IDP accelerates document processing, leading to quicker response times and more efficient service, thereby enhancing the overall customer experience.

Can IDP be used in the healthcare, insurance, and finance industries?

Yes, IDP has a wide range of applications in both healthcare and insurance industries, aiding in efficient document management and compliance. Financial institutions use IDP to automate repetitive tasks in document handling, improving accuracy and efficiency while reducing the dependency on manual processes.

What role does deep learning play in IDP?

Deep learning enables IDP solutions to understand and process complex document formats, making them more efficient and accurate.

Is human intervention still necessary with IDP?

While IDP significantly reduces the need for manual processing, human oversight is still important for quality control and handling exceptional cases.

How does IDP affect business users?

IDP streamlines document-related tasks for business users, allowing them to focus more on strategic activities rather than manual document handling.

How does IDP ensure the confidentiality of customer details?

IDP systems like prioritize data security, using encryption and secure protocols to protect customer details during document processing.

What is the role of IDP in processing files on a daily basis?

IDP automates the processing of files daily, significantly reducing the time and effort required to handle large volumes of digital documents.

What are the key steps of document processing in IDP?

The steps include document intake, converting documents into a machine-readable format, data extraction and analysis, and integrating the processed data into business systems.

Can IDP handle digital documents differently from traditional paper documents?

Yes, IDP systems are adept at handling digital documents, leveraging their format for more efficient and accurate processing.

How does IDP contribute to accurate document processing?

IDP uses advanced algorithms and deep learning to ensure high accuracy in data extraction and processing, minimizing errors that are common in manual processes.