A leading die and mold manufacturing company needed to optimize the manual process of identifying equivalent references between products from different manufacturers. This repetitive and error-prone task was time-consuming and posed a financial risk of errors. The need to respond quickly to customer requests required an automated and accurate solution.
The SIBAR system (Automated Reference Search System) was developed, based on mathematical algorithms and Artificial Intelligence techniques. This tool makes it possible to insert texts with product references and automatically obtain their equivalences in the digitalized catalogs of the client and its main suppliers. A common reference framework was thus created that facilitates the interpretation of orders and improves operational agility.
We developed SIBAR, an AI-based system that identifies equivalent references among manufacturers, reducing errors, speeding up responses and optimizing commercial and logistics management.
- Catalog digitization: Automated integration of own and third party references.
- Error reduction: Minimization of risks associated with human error in product identification.
- Time savings: Reduced manual effort and faster response to customers.
- Increased operational capacity: Improved logistical efficiency and expanded commercial potential.
