The project
A retail company facing a rapidly growing volume of email orders needed a system to drastically reduce manual data entry into its ERP. The project involved building an AI-driven pipeline capable of analyzing emails in multiple formats (including PDF attachments, Word documents, spreadsheets, and images), extracting relevant information, and automatically transforming it into structured orders ready for ERP integration.
The methodology combined several technological components:
- Text extraction via NLP
- OCR parsing for visual content
- Semantic analysis with LLMs to identify key data entry fields
- Data preprocessing and cleansing
- Automated customer and product matching
- Final ERP upload through dedicated APIs
Results
The automation of the process led to a 90% reduction in time spent on manual email order entry, freeing up operational resources and minimizing data entry errors.
The solution streamlined the order management workflow, increasing customer response speed and ensuring stronger integration between sales channels and the ERP system. This transformation turned a traditionally time-consuming and fragmented process into a scalable digital asset with high operational impact.
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