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Butlr launches thermal-sensing products for occupancy and restroom cleaning
Ask Butlr provides anonymized insights on occupancy, dwell time and energy use, while the Smart Cleaning module targets restroom cleaning costs using door-swing data.
Physical artificial intelligence company Butlr has launched two new products for building operators, Ask Butlr and its Smart Cleaning module, aiming to improve space utilization and reduce facility costs.
Butlr, an MIT spinout, uses wall- or ceiling-mounted thermal body heat sensing and machine learning to infer human behavior without cameras or other privacy-compromising methods. According to Commercial Observer, Ask Butlr analyzes anonymized thermal sensor data and integrates it with AI to produce insights on building occupancy, dwell time, foot traffic and energy consumption, with outputs intended to support space planning, operations and capital real estate investment decisions.
The Smart Cleaning module, also part of Butlr’s spatial intelligence platform, is designed to lower restroom cleaning expenses. Commercial Observer reports the system captures foot traffic and occupancy data outside restrooms, then adds deeper insight based on bathroom door swings, with an optional touch module for staff to confirm cleanings are complete and a closed-loop workflow that directs teams where to focus.
The company said it built Ask Butlr in response to demand for accurate first-party building data without compromising occupant privacy, and cited a Wakefield Research survey it commissioned. Commercial Observer reports the survey found that 24 percent of unoccupied office space still gets heated and cooled, and 66 percent of building managers clean all areas at the same frequency.