Predictive maintenance platform that prevents elevator breakdowns for building managers ($5M ARR)

Elevator breakdowns cost building managers thousands in repairs and furious tenants. ElevatorSense uses IoT sensors and machine learning to predict failures before they happen, turning reactive "fix it when it breaks" into proactive "catch it before it fails." You get real-time health scores, maintenance alerts, and cost forecasts that help you schedule repairs during off-hours instead of emergency weekend calls. The platform targets the overlooked mid-market: buildings with 2-20 elevators that can't afford enterprise solutions but are drowning in maintenance costs. At $299 per building monthly, you're solving a $61B market where most managers still rely on outdated service contracts and reactive repairs. You start with simple IoT retrofits that plug into existing elevator systems, then layer on analytics that show exactly when components will fail. You grow through property management LinkedIn groups, elevator technician forums on Reddit, and SEO for "elevator maintenance costs." The wedge is cost savings, the expansion is building operations. Once you prove ROI on elevators, you become the predictive maintenance platform for HVAC, fire systems, and security equipment. Property managers who save $50K annually on elevator repairs will trust you with their entire building's mechanical systems. Start with pilot programs at 10-15 mid-sized properties, install basic vibration and temperature sensors, and prove you can predict failures 2-4 weeks in advance. That's your proof of concept for scaling to hundreds of buildings that desperately need modern maintenance intelligence without enterprise complexity.

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