Most urban fleet platforms treat simulation and live operations as separate problems. Switch splits its intelligence across three products that don't naturally talk to each other without manual handoffs, which means insights from planning simulations don't automatically flow into real-time routing decisions.
But Switch does solve a genuine fleet problem. It forecasts demand with 98% accuracy, then uses that data to rebalance vehicles before shortages happen. Cities running shared bikes, car rentals, or last-mile delivery can see where demand will spike and move assets there preemptively. The digital twin feature lets operators test infrastructure changes before spending money on new parking hubs or charging stations.
The routing optimization works in real time — fleets don't just get a morning route plan. They get continuous adjustments as conditions shift. The system combines historical patterns with live data to decide which vehicle goes where, when to pull units from service, and how many assets each zone needs.
Fleet sizing gets specific attention. Operators can model different fleet sizes against forecasted demand to find the balance between service coverage and cost. The synthetic data solutions help when real-world data is sparse or inconsistent.
Switch targets shared micromobility companies, car sharing services, third-party logistics firms, last-mile operators, rental companies, vehicle manufacturers, local governments, and consultants. Each stakeholder can run what-if scenarios on policy changes or operational tweaks before committing resources.
The mobile app and API access mean field teams and backend systems can both tap into the same intelligence. Infrastructure planning extends to EV charging station placement, not just vehicle distribution. It's built for the complexity of urban logistics where demand shifts by hour and neighborhood.
