Difinity Digital transformed manual PDF data extraction into an intelligent, automated workflow for one of the leading electronics manufacturers.
The client’s engineering teams manually reviewed thousands of PDF datasheets to extract product specifications, dimensions, and ordering details; a slow, repetitive, and error-prone process.
Each datasheet had inconsistent formatting, nested tables, and technical diagrams, making standard automation tools ineffective. Manual Excel population also introduced inaccuracies in part numbers and dimensions. With 35+ new datasheets added each year, scaling this process became unsustainable.
“Processing thousands of datasheets manually was draining our team’s time and increasing the chance of errors. The shift was immediate. We went from slow, manual processing to an automated system that handles even the most complex datasheets with precision. Difinity Digital didn’t just speed up our workflow, they helped us eliminate errors and scale effortlessly. It’s one of the most effective automation initiatives we’ve implemented.”
The client saw a clear opportunity to replace their slow, manual extraction process with an intelligent system capable of understanding complex documents. They needed a solution that could interpret varied datasheet formats, eliminate human errors, standardize outputs, and scale effortlessly as new product lines were introduced. Difinity Digital stepped in to build a future-ready extraction engine that could keep pace with their global operations.
The client relied on manual extraction of specifications and ordering details from thousands of PDF datasheets, each with different formats, nested tables, and technical diagrams. This inconsistency made automation nearly impossible and left teams spending hours interpreting documents and populating Excel sheets. As product volumes grew, so did errors, delays, and the inability to scale the process effectively. The combination of unstructured data, complex layouts, and rising workload created a clear operational bottleneck.
Difinity Digital built an automated extraction system using PyTesseract OCR to convert PDFs into readable text and Google Gemini LLM to interpret complex layouts, nested tables, and technical details. A dynamic logic engine handled ordering permutations, while Pandas and OpenPyXL standardized the output and performed automated validations. The entire workflow ran on a scalable, integrable architecture that connected seamlessly with downstream ERP and quotation systems, delivering fast, accurate, and future-ready
“Our aim was to make document extraction as intelligent as possible, not just faster. By combining OCR with large language models and rule-based logic, we built a system that understands data like a human but works at machine speed. This project is a perfect example of how AI can simplify complexity.”
Manu George Michael, Director, Difinity Digital
–from Execution Team