Case Study: South China Morning Post achieves faster image search and improved discoverability with Looker

Leverages AI through Project Dali to classify millions of images

South China Morning Post, Hong Kong’s journal of record, needed a better way to search and manage a repository of millions of untagged images. Manual tagging was slow, costly, and inconsistent, making it hard for newsroom teams to find people, places, and other entities quickly. The publisher turned to Looker as part of its Google Cloud-based data and analytics environment for better visibility into its content workflows.

Looker helped South China Morning Post support a solution that automated image classification and tagging at scale, alongside Google Cloud tools such as Google Kubernetes Engine, Cloud Storage, and Cloud SQL. The result was a prototype that could recognize faces and other entities, reduce manual tagging effort, and improve searchability and SEO. South China Morning Post said the initiative would save time for editors and content teams, with the broader goal of making image discovery faster and more accurate.

South China Morning Post

Korey Lee

Head of Data