This case study shows how a leading U.S. pulp and paper manufacturer used MultiSensor AI to prevent fires and reduce unplanned downtime in a high-risk sawmill environment. After a costly fire event, the facility deployed fixed thermal cameras and AI-driven monitoring across critical assets and ignition-prone zones. The result: a 62% reduction in asset failures, zero thermal incidents since implementation, and more than $550,000 saved in avoided downtime within the first year. By shifting from reactive inspections to continuous early fire detection, the operation improved safety, increased throughput, and strengthened long-term asset reliability.