Who makes detection for AI data centers

Detection is the part of fire safety that decides whether an event is a repair or a rebuild. Conventional spot detectors wait for smoke to reach the ceiling; aspirating systems continuously draw air through a pipe network to a central detector sensitive enough to catch the products of overheating long before anything is visible. In a hall with very high airflow, that difference is decisive, because dilution can keep smoke below a spot detector's threshold while a fault develops. Air movement is the design problem throughout this part. Sampling points have to be placed where the air actually goes, which means at return paths and inside cabinets rather than only at the ceiling, and the system has to be commissioned against the room's real airflow rather than a drawing. Detection is also increasingly placed inside electrical rooms and battery rooms, where the failure modes are different and earlier warning is worth more. AI density raises both the power concentrated in a hall and the airflow through it, which pushes further toward aspirating detection. What to look for is sensitivity class and where sampling is done, whether detection is integrated with the suppression release and the building management system, and how the site handles the alarm chain — very early warning is only useful if there is a defined human response to a pre-alarm that does not involve discharging anything.