Challenge
A leading doors, windows, frames, and glass manufacturer relied on manual review of complex PDFs, often 30+ pages containing technical specs critical to production planning and third‑party integrations. The mix of system‑generated files and scanned supplier documents demanded deep domain expertise, slowing throughput and introducing errors.
As volumes grew, delays and data inconsistencies increased, and the process became dependent on a handful of specialists. Constantly evolving document formats further amplified risk and inefficiency.
Solution
We implemented an intelligent, cloud‑first automation built on Microsoft Power Platform and Azure. SharePoint serves as secure intake; Azure Functions orchestrate serverless processing; and Azure OpenAI performs domain‑tuned extraction.
When a PDF is uploaded, pages are converted to images and analyzed by a custom AI model, results are returned as structured JSON, then automatically cleaned and transformed into standardized Excel templates for seamless integration with third‑party systems.
Power Automate coordinates ingestion, extraction, and template generation, with a QA layer monitoring accuracy and adaptation to changing formats.
Business Value
The impact was immediate and measurable: processing time per document dropped by 90%, from ~2 hours to 12 minutes, while manual data entry was eliminated, driving a 100% reduction in extraction‑related errors. Employee productivity rose 60% as teams shifted from repetitive data work to higher‑value tasks.
Each document now yields 5+ standardized Excel outputs, ensuring consistent data exchange, and the system scales to more than 300 documents monthly with sustained quality.
Download the full case study to see the architecture, model‑training approach, and QA framework that made these results repeatable.
