Telangana Deploys Facial Recognition to Automate Attendance According to the World Bank AI Repository case study, Telangana public schools use a mobile app workflow that enrolls student and teacher facial templates to automate attendance. The system captures classroom photos or selfies, matches faces to enrolled profiles, and syncs results to a central database for monitoring, per the repository. The case study identifies the deploying organisation as the Telangana school education department and the developer as RNIT Ai Solutions, and reports the solution is fully deployed and closed-source. The repository states 2.1 million facial templates are processed daily in Telangana. The technical description notes cloud-based inference, a live connection requirement, and uncertainty about whether the implementing firm fine-tuned or retrained a base computer vision model, per the World Bank entry. What happened According to the World Bank AI Repository case study, Telangana public schools have deployed a facial-recognition system to automate attendance. Per the repository, the workflow uses a mobile app where schools enroll student and teacher facial templates, then capture attendance via classroom photos (group attendance) or selfies (self-attendance) that are matched to enrolled profiles and synced to a central database. The case study lists the Telangana school education department as the deploying organisation and RNIT Ai Solutions as the developer, and records the deployment as fully deployed and closed source. The repository reports 2.1 million facial templates are processed daily in Telangana. Technical details Per the World Bank entry, the user interface is an app for teachers that connects to cloud-based inference using a computer-vision model tied to a school-specific database of uploaded face data. The case study flags uncertainty about whether the implementing firm fine-tuned or retrained an existing model versus re-using an off-the-shelf model, and notes a live network connection is required for operation. The repository classifies