Think of a large building as a car with cruise control and lots of sensors. This software is like an intelligent autopilot that constantly watches how the building uses electricity, heating and cooling, then automatically tweaks the controls to keep people comfortable while using as little energy as possible.
Commercial and smart buildings waste significant energy because HVAC, lighting, and other systems are run on fixed schedules, crude rules, or manual overrides instead of real‑time usage and weather data. This solution applies AI to continuously optimize energy use across systems, cutting waste without sacrificing occupant comfort or safety.
Tight integration with building management systems and historical operational data, plus domain-specific control algorithms tuned to particular building types and climates, can form a defensible moat. Vendor stickiness also comes from embedding AI into day‑to‑day facility workflows and achieving measurable energy savings that are hard to replicate quickly.
Hybrid
Time-Series DB
High (Custom Models/Infra)
Real-time data ingestion and model inference latency across many buildings and subsystems, plus data integration and privacy constraints with legacy building automation systems.
Early Majority
This approach combines traditional smart building control software with AI that learns from each building’s historical patterns (occupancy, weather, tariffs, equipment behavior) to automatically optimize setpoints and schedules at a granular level, going beyond basic rule-based building automation or static energy management dashboards.