Case Study: Globis predicts shipment arrival times with Peliqan

How Globis SaaS ERP activates customer data to predict container arrivals using machine learning

Globis, a cloud-based ERP platform for managing complex intermodal supply chains, faced significant challenges in predicting shipment delays. Their data infrastructure was unable to enrich internal data with external sources like weather and geolocation, centralize information, or deploy machine learning models. They partnered with Peliqan to address these issues.

Peliqan's platform provided a built-in data warehouse to unify data from Globis's ERP and external APIs. Using Peliqan's low-code tools, the team developed and tested machine learning models and then deployed the final model as a production-ready API. This solution saved the customer over 50 hours per month, connected more than five SaaS sources, and enabled the testing of 10 different ML models.

Globis