AI New Construction Tracking
The Problem
“You can’t manage what you can’t see—construction progress and building risks are fragmented”
Organizations face these key challenges:
Project status lives in emails/spreadsheets, so leadership finds out about delays and safety issues too late
High variance in reporting quality across GCs/sites; risk identification depends on who’s on the job
Teams spend hours reconciling schedules, drawings, RFIs, and field notes into “one version of truth”
Building ops goes reactive after handover: alarms, comfort complaints, and equipment failures drive unplanned work
Impact When Solved
Real-World Use Cases
AI Predictive Maintenance for Commercial Buildings
This is like giving a commercial building a smart “check engine light” that looks at all the sensor data (HVAC, elevators, lighting, water systems) and warns you before something breaks, instead of after tenants complain or systems fail.
Building Automation: Artificial Intelligence and Machine Learning
Think of this as a smart building autopilot: software that constantly watches how a building uses electricity, heating, cooling, and lighting, then automatically tweaks the controls to keep people comfortable while using as little energy as possible.