The Future is IDP. Are You Missing Out?

Welcome to the first step in transforming your business with Intelligent Document Processing (IDP). If you’re here, you’ve probably realized something critical: your team’s work alone is no longer enough to stay competitive in today’s fast-paced world. You need to get more work done in less time. Expanding your team is the most non-feasible way, especially for document-heavy industries like insurance, and mortgage to process data from a large variety of documents. While automation has been around for some time, we're now entering a new era—one where systems don't just automate tasks but actually understand and learn from the data they process. This evolution is called Intelligent Document Processing (IDP). In this blog, we’ll walk you through how IDP works, and how to integrate it into your business for optimal results.

Intelligent Automation 

Whether it’s mortgage approvals, insurance claims, or manufacturing reports, data-heavy industries face a common challenge—processing massive amounts of information efficiently. And this problem isn’t going away anytime soon. In fact, it’s growing. According to recent studies, around 70% of all documents worldwide are unstructured. Think of handwritten notes, PDFs, scanned images, complex forms, tables, diagrams, and whatnot.

For years, companies have turned to tools like Optical Character Recognition (OCR) to digitize and automate their workflows. But here’s the catch—OCR was designed to extract text from images, not interpret complex, unstructured documents. This means it often falls short, especially when documents don’t fit the same template every time. And when OCR fails, businesses are left with costly manual processes, operational delays, and increased error rates.

That’s where Intelligent Document Processing IDP comes in.

What’s IDP?

IDP (Intelligent Document Processing) is an advanced AI-powered technology designed to extract, classify, and process complex data from various document types. It uses machine learning, natural language processing (NLP), and computer vision to handle unstructured or semi-structured data.

Unlike traditional methods like OCR, IDP can understand context, capture complex information, and learn continuously, making it ideal for automating document-heavy tasks.

Why OCR Isn't Enough Anymore

You’ve probably used OCR at some point, and it worked great for simple tasks like scanning printed documents or turning a paper form into digital text. But things get tricky when OCR encounters more complex, unstructured data. Maybe it’s a mortgage file with a mix of handwritten notes, printed forms, and scanned images. Or an insurance claim filled out in varying formats across different states. OCR struggles to make sense of this. It can’t “think” or understand the context of the document, which is where things tend to break down.

And that’s the problem. OCR was built to digitize data, but in today’s world, businesses need more than just digital copies of documents. They need systems that can understand the information within those documents and turn it into something actionable to be directly fed into their systems for further processing. But OCR makes this impossible without significant manual intervention which sometimes can cause you more than just manual extraction.

The Cost of Traditional Data Extraction

The ongoing challenge of finding and retaining skilled data entry workers, especially in the wake of the pandemic, has only intensified. High turnover in these roles means that when experienced employees leave, they take years of accumulated knowledge with them. New hires require significant time and resources to be trained from scratch, which disrupts workflows and adds to operational costs.

This constant cycle of hiring, training, and replacing staff is not only inefficient but also expensive. According to industry reports, businesses that rely on manual data processing face at least 50% higher operational costs compared to those that have implemented intelligent automation.

Adding to the issue, humans inevitably make mistakes. In critical industries like finance, insurance, and mortgage lending, even minor errors such as misfiled documents, missed deadlines, or incorrect data entries can have serious financial repercussions, including lost revenue and compliance fines.

Despite these clear challenges, many businesses continue to hire and retrain teams for document processing, relying on traditional tools like Optical Character Recognition (OCR). 

Considering the rising costs, inefficiencies, and risks associated with human error, can your business continue relying on traditional methods—especially when industry leaders have already adopted more effective, scalable, and accurate solutions?

The Solution

Imagine this: your document processing system doesn’t just scan and digitize text. It reads and understands it, no matter how complex or unstructured. Whether it’s a handwritten note, a detailed financial report, or a multi-format insurance claims document. Yes, it is now possible with Intelligent Document Processing (IDP).

Unlike traditional OCR, IDP leverages AI and machine learning to learn from every document it processes. It can handle complex, unstructured data and extract insights with accuracy comparable to human intelligence. This means faster turnaround times, fewer errors, and a system that gets smarter the more you use it.

The best part? IDP is flexible. It works with any type of document, across industries, without the need for rigid templates. From insurance and mortgage to manufacturing and construction, businesses are adopting IDP to streamline their workflows, reduce operational costs, and outpace their competitors.

Business Leaders Are Already Adopting IDP—Shouldn’t You?

The top 5% of companies across industries like finance, insurance, and real estate have already integrated IDP into their processes. Automation could save businesses up to $2.7 trillion annually by reducing inefficiencies and improving accuracy.

These companies are already seeing the benefits—faster processing times, lower costs, and an ability to handle much larger workloads without scaling their teams. By using IDP, they’ve positioned themselves to take advantage of future growth while their competitors are still grappling with old, manual processes.

Where Will Your Business Be?

As more and more industries make the shift to intelligent automation, the question is no longer if you’ll automate but when. If you don’t, you risk falling behind in a market where speed, efficiency, and accuracy are more important than ever. The IDP market is projected to reach $49 billion by 2026. This means more and more businesses like yours are likely to enable IDP to scale their operations. The future of business isn’t just about automating processes—it’s about doing it intelligently.

Surveys show that 73% of companies expect to fully automate document-heavy processes in the next five years to maintain competitiveness.

And that’s where we leave you, for now. We’ll dig deeper into the technical side of IDP in the next chapter, exploring exactly how this technology works and why it’s uniquely positioned to solve the challenges businesses face today.

The Science Behind IDP – How it Works and Why it Matters

Intelligent Document Processing isn’t just about automation—it’s about creating smarter workflows. Here’s how Infrrd’s IDP works: (flowchart-for designers)

1. Document Preprocessing

The documents ingested from various sources like emails, and documents for other integrated systems are made processing ready in the preprocessing stage that involves skew correction, noise reduction, clarity enhancement, etc. This ensures a smooth trouble free extraction process.                                 

2. Document Classification

Documents are automatically classified by AI and machine learning models, supporting multiple languages and tailored to diverse business needs. Infrrd’s document classification models efficiently handle both document-level and page-level classification across various use cases.  

3. SLA Management                                                                                                           

The system automatically prioritizes documents based on your Service Level Agreements (SLAs) and moves urgent files to the front of the queue, making sure your team never misses a deadline.

4. Data Extraction 

Infrrd IDP combines OCR with the human-like intelligence of ML algorithms (Machine Learning) to extract text, numbers, images, and tables from invoices, paychecks, and diagrams with the highest accuracy, irrespective of the fluctuating volumes and document formats.

5. Data Corrections with HITL

The extracted data is automatically verified against set rules, flagging discrepancies for review. Flagged data is thoroughly reviewed by Infrrd’s HITL (human-in-the-loop) from Infrrd’s team. We carefully correct any errors, ensuring the final results you get are completely accurate.

6. System Integration

Infrrd IDP easily integrates with your ERP, CRM, and other systems, streamlining your workflows without the hassle.

7. AI Assistant - Annie

Meet Annie! She automates post-processing tasks like report generation, calculations analytics, and a lot more. Want to get a bigger picture of what Annie can do? Let us show you how she can simplify your work. Book a demo with our AI Experts here.

8. Feedback Loop

Errors are fed back into our system to enhance learning, making our processes smarter and more efficient.

How to Leverage the Next Big Thing in Automation for Your Business

In this section, we’ll guide you on how to maximize the potential of Intelligent Document Processing (IDP) for your business. You’ll discover practical ways to integrate IDP into your workflows to boost efficiency, cut costs, and enhance decision-making through data-driven insights.

Here’s how to get started in 8 simple steps:

1. Know Your Document Types

Assess the types of documents your business handles. This depends on your industry and field of expertise. Classify your documents based on their format—whether they are text-only, handwritten, tables, a mix of tables and text, or more complex formats like engineering drawings.

2. Test the Waters

Identify where errors frequently occur in your data extraction process. For example, in the construction industry, your team might face difficulties extracting data from handwritten notes or technical drawings using traditional OCR. Narrow down your most significant data extraction challenges.

Tip: Ask your team where they spend most of their time correcting errors.

3. Set Clear Objectives

Once you’ve analyzed the problem areas, define specific goals for your team. For instance, determine how many documents your team can process in the same amount of time with automation. Setting goals can be more complex than it seems. Make sure your team analyzes all aspects of the data extraction challenge before finalizing objectives.

4. Crunch the Numbers: Measure Your ROI

Assess your current ROI and compare it with the potential savings from implementing IDP. Invest in an IDP solution that can at least double your ROI. Use the trial period to verify this before making a final decision.

Tip: Ask your IDP vendor to provide a guaranteed ROI figure based on their AI tool’s performance. For eg, Infrrd IDP can guarantee up to 11x ROI depending upon your business.

5. Use IDP as a Backup, Not a Replacement

AI-powered IDP can automate repetitive tasks, but it’s not a replacement for your entire data processing team. Infrrd IDP features a user-friendly interface that anyone can operate, even without coding skills. Train your team to master IDP so they can handle their routine tasks independently.

6. Test and Trial

Investing in a data extraction system is a big decision. Take advantage of the trial period to see how the system works with your specific documents before committing fully.

7. Prioritize Data Safety

Ensure you understand how your documents are treated during the data extraction process. An ideal IDP system should be transparent about document handling and ensure confidentiality. For instance, at Infrrd, documents are automatically erased from the system once extraction is completed.

8. Balance Accuracy with Speed

When selecting an IDP solution, choose one that strikes the right balance between accuracy and speed. For example, Infrrd offers an average accuracy of 70% on the first go with No Touch Processing and 100% accuracy with Human-in-the-Loop review.

 Tip: Prioritize systems that deliver both high accuracy and quick processing speeds.

In a Nutshell

Intelligent Document Processing (IDP) is the smarter way forward for data automation. It’s nothing new, but your OCR with human intelligence. Unlike OCR, which struggles with messy, unstructured documents, IDP actually learns and improves over time, making it perfect for today’s complex business needs. It’s faster, more accurate, and doesn’t rely on rigid templates.

For companies looking to integrate IDP, the process is straightforward: know your documents, identify the pain points, set clear goals, and measure the return on investment. Done right, IDP won’t just save you time—it’ll make your team more productive and help you stay ahead in an increasingly digital world.

If you’re still relying on manual document processing, now’s the time to make the shift to smarter automation. The future is here, and it brings new meaning to intelligence you don’t want to miss.

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