AI Make-Ready Scheduling
The Problem
“Make-ready scheduling is costing you vacancy days because dependencies are managed in spreadsheets”
Organizations face these key challenges:
Turnovers slip because inspections, parts, repairs, and cleaning aren’t sequenced with real dependencies
Schedulers spend hours daily rescheduling around vendor no-shows, access issues, and surprise scope changes
Work orders live in multiple systems, so crews arrive without the right parts, context, or approvals
Missed rent-ready dates create vacancy loss, concessions, and frustrated leasing teams/tenants
Impact When Solved
Real-World Use Cases
AI for Commercial Real Estate Decision-Making
Think of this as a super-analyst for commercial real estate that never sleeps: it reads huge amounts of market, property, and financial data and then suggests which buildings to buy, sell, lease, or invest in, and at what terms.
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.