Enhanced border security

The customer challenge was that a sophisticated customs department, managing how goods were imported and exported into the country, wanted to leverage AI models to identify risky goods entering the country, while also reducing the number of false positives in identifying these risky goods. The client was using a rules-based engine to identify risky goods. However, the vast majority were false positives, which resulted in needless inspections and slowed down the entire customs process.

With Cloud Pak for Data, this customer was able to build a unified platform to handle all of their data science needs – from discovery to deployment. They used platform connectivity to gain access to existing sources of data, the Watson Studio service to train ML/AI models, the Watson Machine Learning service to deploy and operationalize the models, and Watson OpenScale to monitor these models and understand the logic behind them.

The following diagram represents...