Every vehicle.
Every hour.
Earning more.
AI that dynamically orchestrates fleets in real time to maximise utilisation and revenue per vehicle.
Tens of thousands of ride-hailing vehicles.
Millions of individual decisions.
No city-wide central intelligence.
Vehicles cluster around the same demand while entire areas remain unserved.
Congestion increases. Utilisation falls. Revenue is lost.
In autonomous fleets, solving this becomes critical for profitability.
One AI.
Every vehicle.
The whole city.
Odysse uses reinforced learning to dynamically orchestrate fleets in real time, maximising utilisation, revenue per vehicle, and fleet efficiency across entire cities.
The AI sees the city.
The fleet follows.
Odysse distributes vehicles across the city in real time, ahead of demand. Every trip, movement, wait time and outcome feeds back into the model. Odysse never stops learning.
Proven on human fleets.
Ready for AVs.
Odysse’s model has been trained on three years of data from real London streets, learning from edge cases, top-driver behaviour, waiting patterns and demand shifts to make every fleet decision sharper.
The actuator changes. The intelligence stays.
The autonomy case →