
Fleet & logistics
Fewer incidents, lower cost per vehicle.
Every vehicle generates behaviour data. On-device AI turns it into a risk profile without the data leaving the driver's hardware. You see the patterns, the driver keeps their privacy.
Solutions
One platform turns on-device behaviour data into safety intelligence — for fleets, insurers, transit, regulators, and ride-hailing. The driver's raw data never leaves their device.
01 — The platform
Signals come in from the hardware a vehicle already carries. Two AI layers — L-DBA for driver behaviour, L-IMN for network intelligence — turn them into safety intelligence for eight sectors. Raw personal data never leaves the device.

02 — Who it serves
Fleet safety is where we start. The same platform serves everyone who carries the risk of the road — each reads the intelligence, none sees the driver's personal data.

Fleet & logistics
Every vehicle generates behaviour data. On-device AI turns it into a risk profile without the data leaving the driver's hardware. You see the patterns, the driver keeps their privacy.

Insurance & repair networks
Pre-incident behaviour and impact data through an architecture that clears your data-sharing thresholds.

Public transport & transit
Network intelligence for safer service. Your drivers and your riders stay out of the data.

Road authorities & regulators
Anonymised, aggregated evidence for regulation and planning — without watching anyone.

Ride-hailing
Behaviour profiles that serve the platform's duty of care and the driver's privacy at the same time.
03 — Integration
The edge model runs where the vehicle already has compute. No new hardware to buy, and three ways to bring it into your stack.
The data collection app runs on the hardware drivers already carry. Nothing to install in the cab.
Embed the edge model on the telematics unit or the vehicle's own compute for always-on profiling.
Partners integrate the model through SDKs and pull anonymised network intelligence over APIs.
04 — Pilot programme
A commercial engagement with defined scope, fixed duration, and success measures we agree before anything is installed.
01
We agree the fleet, the sites, and the success measures up front.
02
The app or edge model goes live on your existing hardware — nothing new to buy.
03
You see behaviour patterns and incident trends against the measures we set.
Start the conversation
Talk to us about a pilot — defined scope, fixed duration, success measures we agree before anything is installed.