AI is the driver. Here is how it thinks.
No mystery and no buzzwords. This is what our vehicles sense, how they decide, and the infrastructure that lets us test every change before it reaches the road.
A driving stack that reads the road object by object.
Drivora's core is a set of models trained on real driving data to see, predict and plan — each one small enough to run on the vehicle, in real time.
What the vehicle senses
Eight cameras, a roof lidar and four corner radars give overlapping 360° coverage — so no single sensor failure leaves a blind spot.
What it detects
Vehicles, pedestrians, cyclists, lanes, signals, signs, debris and roadworks — each with a position, speed and confidence score.
How it decides
A prediction model forecasts several possible futures for every road user; the planner picks the smoothest path that stays safe in all of them.
Why it improves
Every tricky moment on the road becomes a test case in simulation — the fleet's experience compounds with every mile.
From a sensor reading to a steering command.
Sense
Camera, lidar and radar frames.
Fuse
Align everything into one 3D scene.
Perceive
Detect and track every object.
Predict & plan
Forecast others, choose a path.
Act
Smooth steering, throttle, brake.
On-board compute, cloud simulation.
Decisions happen on the vehicle in milliseconds. Learning and testing happen in the cloud, at scale.
On the vehicle
- Automotive-grade GPU computer running the full stack
- Redundant power and a fallback controller that can always stop safely
- No network connection needed to drive
In the cloud
- Millions of simulated miles replayed before each software release
- Model training on labelled fleet data
- Encrypted fleet data, kept in your region
The gap finally closed.
Affordable lidar, powerful on-board GPUs and realistic simulation now make supervised autonomy practical on repeatable fleet routes.
Who we serve.
Logistics and delivery fleets, transit and shuttle operators, ride-hail platforms, and ports and private sites — priced per vehicle.
Where we honestly are.
Early stage. Closed-course validation is under way, and we are recruiting partners for supervised pilot routes.
What we are building next.
| Phase | Focus | Status |
|---|---|---|
| 1 | Perception & planning on closed courses | In progress |
| 2 | Supervised pilot routes with partner fleets | In progress |
| 3 | Night and wet-weather operation | Next |
| 4 | Driver-out on private sites | Planned |
| 5 | Remote-assist at fleet scale | Planned |
| 6 | Public-road driver-out, route by route | Future |