Manufacturers and operators of large display walls needed proactive quality monitoring from EOL through deployment to reduce field failures and service costs.

Image capture + CV pipelines, remote metric collection, and correlation with monitoring data.

Time‑series AI to predict likelihood of hardware issues; reporting and email alerts for technicians.

Pattern recognition; regression & classification models; autoencoder + GRU for anomaly and temporal patterns; Influx for time‑series storage; OpenCV for CV processing.

Earlier detection of display quality issues; fewer emergency callouts.

Traceable quality metrics across manufacturing and field operations.

Autoencoder, GRU; Influx; OpenCV