Mobility as a Service (MaaS)

Ride-hailing and ride-sharing services are replacing privately-owned automobiles as Mobility as a Service (MaaS) leads a new economy fueled not by vehicle manufacturing, but by vehicle telematics data. Iconic automotive brands and visionary shared mobility start-ups turn to HEAVY.AI to drive new carsharing telematics data use cases and gain competitive insights from big data mobility analytics in the Mobility Industry.

  • 21% of Americans claim the availability of shared mobility has allowed them to delay or avoid purchasing a car
  • 63% percent of Americans expect to increase their use of ride-hailing services in the next two years
  • In 2015, 15% of Americans used ride-sharing services; in 2018, that number grew to 43%

Whitepaper: Find Opportunity & Risk Hidden in Your Enterprise

Make time-sensitive, high-impact decisions with Big Data and HEAVY.AI


Visualize and Analyze Shared Mobility Fleet Telematics Data in Milliseconds to Optimize Ride-Sharing Services

Through HEAVY.AI's accelerated analytics, data scientists, analysts, and policy-makers can now instantly visualize and analyze tremendous volumes of telematics data streaming from automobiles, mass transit, bikes, scooters, and beyond. This unlocks a wealth of new business and government use cases to capture the value from vehicle telematics data streams, optimize transportation and logistics, and improve city planning and shared mobility infrastructure.

  • Visualize millions of carsharing, e-hailing, bikesharing and delivery geo points to identify congestion and optimize safe new pick-up and drop-off zones
  • Improve urban mobility and reduce automobile traffic by layering disparate automobile, bike, and scooter telematics datasets to identify new opportunities for microtransit infrastructure
  • Optimize deployment of shared mobility fleets, track usage, and increase uptime through preventative maintenance
  • Derive spatiotemporal insights from customer behavior and discover relationships between destinations, driving habits, and infotainment preferences

How BMW Visualizes & Interacts with Extreme Datasets with Near Zero Latency

NVIDIA GTC 2019 Presentation

Mobility as a Service (MaaS)

Use Cases