Experiment 01 · live in production
Motion OS. Fleet operations, AI-managed.
Our first live experiment. A working product run in production that proves the platform against the messy reality of running a fleet at city scale.
Why fleet first
Real-time. Human-heavy. Hybrid.
Fleet operations were chosen as Experiment 01 because they are exactly the kind of work where dashboards stop being enough. Decisions are made every few minutes. The team spends the day on calls, messages, and screens at the same time. The cost of being late is real and visible.
If we can run an AI operator inside fleet operations, the platform works for anything similar.
01 · The problem
Reacting late.
Today's operations team uses dashboards, spreadsheets, supervisor judgment, and phone calls. They know what happened yesterday, but they are always reacting late. Traditional fleet software shows screens. The team still has to read them, decide, and act.
02 · What Motion OS sees
The full live picture.
- 01Where vehicles are, in real time
- 02Where demand is rising or collapsing
- 03Which drivers and vehicles are active
- 04Traffic, weather, events, road closures
- 05Underserved zones and at-risk customers
- 06Which supervisors need action — and why
03 · Where it fits
A command center for any fleet that has to move in real time.
More experiments
What comes after Motion OS.
Motion OS is the first vertical we are running in production. Experiments 02 and 03 are already in design and research. The plan is one new live experiment a year, each in a different industry, each one stress-testing a different part of the platform.