AngelList

Continuously monitor and diagnose faults in your facilities to save large amounts of energy, time, & money. In a pilot at UC Berkeley (200k sqft), we saw a 30% overall energy savings ($300K / year) within 6 mths. The building manager clicked through sensor stream data and detected these faults.

Backend developed over 3+ man-years in 2 PhD theses. Unlike competitors, we create a virtual representation of a bldg. and can run various algorithms like machine learning, energy attribution, etc.