AI control for your fleet's charge and dispatch
RideBlitz directs when and where each vehicle charges and how it is dispatched. Reduce idle time and waste while keeping every EV in motion.
EV fleet operations are tougher than they seem
Charging plans, dispatch windows, and energy prices do not align automatically. Those gaps cost operators hours and substantial sums each week.
Peak tariff gaps
Vehicles charge when plugged in, not at the lowest rates. Energy costs rise for no operational reason.
Charge conflicts
A vehicle needed at 09:00 may still charge at 08:45. Dispatchers scramble, customers wait, and SLAs slip.
Scattered visibility
Charge state, location, and demand live in separate dashboards. Coordination takes continual manual work across tools.
One AI layer, total fleet control
RideBlitz connects charging infrastructure with dispatch. It reads demand forecasts, tariff windows, and vehicle state in real time, then decides charging and vehicle placement.
Charge when needed, not by default
The AI reads utility tariffs, station capacity, and coming dispatch demand. It sets each vehicle's charging window to avoid peak rates while preserving range for required trips.
- Live tariff links with local grid providers
- Charge-by times for each vehicle
- Automatic fallback during demand spikes
From fleet data to dispatched vehicle in four steps
RideBlitz continuously reads fleet signals and acts automatically, reducing work for your operations team.
Capture fleet state
Existing systems provide charge level, location, maintenance flags, and driver availability every 30 seconds.
Predict demand
Booking history, upcoming reservations, and live ride requests combine to predict where vehicles are needed and when.
Build schedules
The AI creates charging and dispatch windows that meet forecast demand, avoid peak tariff hours, and reduce total idle time.
Run and adjust
Instructions reach chargers and dispatch tools. When conditions change mid-day, the AI recalculates and automatically sends updated schedules.
What pilot operators tell us
Fleet coordinators and operations leads shared this feedback from their early-access pilot experience.
We lost much of our energy budget through off-peak scheduling errors. RideBlitz fixed that in the first week without manual work from our team.
Dispatch conflicts were real. Drivers arriving to half-charged vehicles happened daily. Now it is rare enough for us to notice.
Two-screen scheduling was standard for us. RideBlitz put everything in one view and ended decisions based on stale data.
See RideBlitz on your fleet data
Book a 30-minute session with our team. We will review your scheduling setup and show how the AI would handle it differently.