A European manufacturer cut RFQ processing time by ~80% and eliminated its biggest operational bottleneck - without replacing a single system.
Problem
A major European manufacturer of custom-engineered products was drowning in a deceptively simple task - reading incoming RFQs.
Every quote request arrived in a different format. Clean PDFs generated from CAD tools. Scanned specification sheets. Photos of handwritten notes and sketches on paper. Each one contained up to several hundred technical parameters that had to be manually interpreted, verified, and entered into the order management system.
The work was slow, error-prone, and - most critically - completely dependent on a handful of experienced employees who were the only ones capable of correctly interpreting complex, multi-format orders. When those people were unavailable, quoting slowed to a crawl. Offers came back late. Revenue walked out the door.
Wyzwanie
The core technical difficulty was achieving high accuracy in extracting order parameters - sometimes several hundred per single request - while maintaining stable performance across wildly inconsistent input quality.
The system had to handle everything from machine-generated PDFs to barely legible photos of handwritten notes in multiple languages. A single misread parameter could mean a wrong quote, a wrong product, or a lost customer.
Rozwiązanie
We designed a multi-component AI system that processes the full spectrum of incoming order formats:
- Multimodal LLM integration (OpenAI API) for text recognition, including handwriting in multiple languages, combined with advanced prompt engineering to ensure consistent extraction across edge cases.
- Fine-tuned computer vision models for detecting specific details on input documents and classifying drawing types.
- Structured output pipeline that processes extracted data and delivers results in JSON format directly to the client's existing order management system - no manual re-entry, no middleware, no system replacements.
The solution plugs into the client's infrastructure as-is.
Wyniki
| Metryczny | Wpływ |
|---|---|
| Parameters per order | 100+ extracted automatically from a single RFQ |
| Processing time | ~80% reduction in quote turnaround |
| System changes required | Zero — full integration with existing infrastructure |
The solution dramatically shortened RFQ response times, improved data entry accuracy, and - most importantly - freed skilled employees from repetitive manual work. They now focus on what actually requires their expertise: assessing technical feasibility, advising customers, and closing deals.
Sound Familiar?
If your team is still manually processing complex orders, burning hours on data entry, or stuck waiting for the one person who knows how to read those specs - this is a solved problem.
