Full trucks = Less CO2
RunBuggy’s technology helps keep car haulers full to eliminate empty trucks
Fully loaded coming and going
RunBuggy’s data science team is constantly developing algorithms and machine learning models that match and group transportation orders, helping shippers reduce cost and transporters maximize earnings. In parallel, these practices abate greenhouse gas emissions and degradation to the natural environment that would otherwise be worsened without the use of our tools.
How We Keep Trucks Full
Machine Learning, advanced analytics, and data science are the tools we use to keep trucks full and minimize emissions.
GPS
GPS data of all trucks and paths can be used to understand driver behavior and influence matching algorithms.
GIS
GIS -based nationwide historical and real-time traffic traffic data allows us to determine trucking specific routes. We can compare the optimal routes to actual data to inform our grouping results
Location Optimization
Location optimization algorithms allow us to direct inventory to markets by combining cost to deliver, speed to deliver, and regional specific sales prices.
Matching Algorithms
Order-transporter matching algorithms allow us to efficiently source drivers by combining internal and external datasets of transporter behaviors and truck details.
