Case studies
Transforming Document Processing with AI
Despite the digital revolution, bureaucracy remains a labyrinth of forms, signatures, and stamped documents. Whether at a government office, a bank, or a corporate back office, we are still trapped in a world where information is buried in PDFs, invoices, and scanned receipts—documents that demand human intervention for a simple reason: handwriting.
Think about the last time you had to fill out a physical form. Maybe it was a delivery slip, a customs declaration, or an official notice. A piece of information—your name, a date, a reference number—was scribbled in a tiny box, destined to be processed later. But what happens next? A human worker reads through the document, searches for that crucial detail, and manually enters it into a system. Now, multiply that by thousands of documents per day. Multiply it by weeks, months, years.
This isn’t just an inconvenience for businesses operating at scale—it is a bottleneck. The inability to quickly and accurately extract information from documents costs time, introduces errors, and clogs processes that should be seamless. Optical Character Recognition, or OCR, was meant to solve this. Yet, the reality is that most solutions still overwhelm businesses with unnecessary text, pulling too much information, too little, or simply the wrong thing. The result? More manual correction, more delays, more frustration.
We took it head-on during Session 15 of the Pi School of AI.
We were approached by an industry partner who was facing this challenge. While we can’t disclose their name due to confidentiality agreements, their challenge echoes across industries. They needed a way to extract handwritten and printed information from scanned documents with near-perfect accuracy—not all the text, just the crucial parts—not slowly but at a pace that could scale.
Extracting Only What Matters
The project unfolded as an eight-week challenge, bringing together a team of brilliant Fellows and expert Mentors to create a solution that redefined what OCR could achieve. The starting point was simple: conventional OCR reads everything—but humans don’t. When you scan a document, your eyes move instinctively to the part that matters, discarding the irrelevant details. That ability, that selectivity, is what the existing technology lacked.
Instead of treating every document as a wall of text, AI was trained to see like a person—to recognise structure, hierarchy, and context. It first had to identify where key information was likely to appear in the document. It then needed to extract only that, discarding everything else. The solution employed a dual-model strategy, using a lightweight OCR system for printed text and a deep-learning model for handwriting. This separation was crucial—while printed text follows a structured format and is easily processed, handwriting is far more variable, requiring a model capable of handling diverse styles and imperfections.
The innovative solution delivered twice the accuracy of its predecessor while slashing processing times to a fraction. What previously took over 1.3 seconds per document was now completed in 0.14 seconds—a 10x improvement in speed. The increase in accuracy from 46% to 86.3% meant significantly fewer manual corrections, translating into reduced operational costs and higher efficiency. With thousands of documents processed daily, the AI-powered system saved critical hours of manual review each week, allowing teams to focus on higher-value tasks. It wasn’t just faster—it was smarter, more precise, and entirely scalable.
Figure 1: AI-powered document processing pipeline, from text detection to classification and extraction.
The Future of AI-Powered Document Intelligence
While the solution was built for a specific challenge, its implications stretch far beyond a single company and across industries. Many businesses wrestle with the same fundamental problem: too much information, too little intelligence. The ability to extract only what matters is not just a technical achievement—it is a competitive advantage.
For banks, it means seamless cheque and loan application processing. For logistics firms, it enables instant verification of delivery confirmations. In healthcare, it transforms how patient records are digitised, reducing administrative burden and improving accuracy. Legal services benefit by extracting key case details from extensive documentation, streamlining research and decision-making. The future of document processing isn’t just automation—it’s precision, clarity, and intelligence.
Figure 2: IDP Adoption across business function and industry. Source: Everest Group Intelligent Document Processing (IDP) Playbook
The demand for AI-powered document processing is surging across industries, driven by the need for efficiency, compliance, and cost reduction. According to Gartner’s Market Guide for Intelligent Document Processing Solutions, the IDP market was valued at $4.8 billion in 2022 and continues to expand as businesses increasingly seek to automate document-intensive workflows (Gartner). Banking, healthcare, insurance, and government sectors are at the forefront of this shift, leveraging AI to eliminate manual processing, enhance accuracy, and improve service delivery. Public administration, for instance, is integrating AI-powered IDP solutions to streamline bureaucratic processes, such as permit applications, tax filings, and public records management.
As organisations move away from manual data handling, IDP adoption is accelerating, leading AI-driven solutions to become a necessity rather than a luxury. Gartner’s insights into the IDP landscape highlight the growing role of automation vendors and AI-powered document intelligence, reinforcing that solutions like the one developed in this challenge are at the core of business transformation.
At Pi School, we work at the intersection of research, experimentation, and real-world application, transforming AI from an abstract possibility into a practical tool for business. Our approach is grounded in rigorous problem-solving, rapid iteration, and collaboration with forward-thinking industry partners. We build AI to solve problems, reduce friction, and let businesses focus on what matters most. Each challenge we take is not just about advancing technology but redefining how businesses operate, eliminating inefficiencies, and unlocking previously out-of-reach capabilities.
If your organisation faces the same challenges and wonders if AI could finally cut through the clutter, we’re ready to explore the possibilities.