Drive efficiencies: Learn where and how your workforce spends time to create more efficient workflows, such as cleaning based on occupancy, finding conference rooms, or streamlining patient discharges in healthcare settings. Create healthy indoors: Model use to determine targeted cleaning protocols through occupancy, environmental, and IAQ data. Use 99.9%+ effective UV-C for reliable surface and air disinfection where spaces are densely occupied. Save energy costs: Dynamically dim HVAC and lighting systems based on demand to protect comfort while reducing energy use up to 40%. Further achieve sustainability through reducing chemical cleaning waste.
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R-Zero is a building intelligence platform that delivers real-time insights on how to optimize indoor spaces and buildings to improve workforce productivity, right-size real estate portfolios, and create operational efficiencies, including reducing energy costs. R-Zero’s industry-leading risk model recommends mobile and autonomous UV disinfection where risk is high, to achieve effectiveness while reducing chemical usage and waste, and reducing carbon emissions to achieve sustainability goals. R-Zero’s platform is instantly accessible, easy to use, and scalable across every kind of space, enabling health systems, commercial real estate, cities, public services, and educational systems to prepare today’s buildings to meet tomorrow's challenges.
Lendlease rewrote its tech procurement process after two vendors promised "out-of-the-box" APIs and one came back with a ~$200K integration quote.
Hannah Baker, engineer at Willow, walks through how DFW Airport built a CBM program that actually stuck, from training a non-technical QA team to triage thousands of faults, to graduating recurring issues into automated work orders, to tracking a single KPI called 'unsuccessfully actioned' that finally gave leadership visibility into whether closed work orders were actually fixing the problem.
Jose de Castro, CTO of Mapped, shows how one of the world's largest retailers moved restroom operations from schedule-based janitorial rounds to condition-based workflows by combining foot traffic sensors, flush counts, soap levels, and occupancy predictions into AI-summarized work orders that land directly in the existing CMMS, with no new dashboards or tools for technicians to learn.
Brad Dameron from the University of Iowa's Asset Optimization Team and Katie Rossman from Clockworks Analytics walk through how Iowa handles 3,500 faults per day without burying their maintenance shops, showing the exact triage, routing, and closeout workflow they built to turn fault detection into planned work orders that look and feel identical to every other work order in the system.
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