Automation that moves like a person, not a script
A proprietary motion model — trained on thousands of hours of real human gestures — synthesizes every scroll, tap, and swipe fresh, on a real handset. To the apps running on it, there's a person holding the phone.
The tells that give a robot away
Apps profile every touch across four layers. Ordinary automation trips at least one — instantly. Our model is built to clear all four at once.
Injected input announces itself as a mouse or a phantom device. Ours arrives as a genuine touchscreen event, from real hardware.
Fingers tremble, curve, and press unevenly. Scripts draw a ruler-straight line at flat pressure. Our model reproduces the human wobble.
People start slow, speed up, and ease off. Robots move at one constant speed. Our gestures accelerate and decelerate naturally.
Emulators and injectors leave fingerprints deep in the stack. PhoneFleets runs on physical phones — there's simply nothing to fake.
Same swipe. Two completely different fingerprints.
A perfect line at unchanging pressure and speed. No human hand can do this — and every app knows it.
A natural curve, pressure that swells and fades, speed that ramps and eases. Indistinguishable from a person.
Why apps see a person, not a program
From thousands of hours of real motion to a live tap
Our proprietary model is trained on thousands of hours of genuine human interaction — curves, pressure, rhythm and all.
The engine generates a brand-new, never-identical gesture for every action — no two are ever the same.
The gesture lands on a physical phone as a true touchscreen event — the way any thumb would deliver it.
It ships on every device in your fleet — no configuration, no scripts to tune. It just moves like you do.