Following distance is the collision cause your telematics cannot see.
Rear-end collisions are the most common at-fault event in commercial fleets, and following too closely is the most preventable cause. Time headway is measurable from forward video alone. That is what we build first.
What a safety manager gets.
Headway exposure, per driver
Not an event count — the share of driving time spent under two seconds of gap, normalised by distance. A driver who spends 30% of motorway time tailgating is a different risk from one who does it twice a month, and event counting cannot tell them apart.
Attributed harsh braking
Each hard brake labelled by what preceded it: closing on a lead vehicle, or an external cause. This turns the noisiest metric in fleet safety into one a driver can be coached on without arguing about it.
Coaching evidence
The clip, the headway trace and the moment of the event. Safety conversations fail when they are a number against a driver's recollection; they work when both parties are looking at the same video.
Your own calibration
Thresholds fitted to your collision record rather than a generic default. Given the sensitivity we publish on the Evidence page, a borrowed threshold is close to meaningless.
What exists, what is next, what is blocked.
Published honestly because it is the first thing a technical evaluator establishes anyway.
Kinematic event layer
Harsh braking, acceleration and cornering from speed and curvature. Debounced, exposure-normalised, trip-boundary safe. This is the substrate — it is deliberately not the differentiator, because an IMU produces the same thing.
Time headway
Seconds of gap to the lead vehicle, continuously, from forward video. The wedge: high value to fleets, unavailable from accelerometers, and directly linked to the most common claim type.
Event attribution & lane discipline
Joining each kinematic event to the scene that caused it, plus lane-keeping consistency and unsignalled weaving — behaviours associated with distraction and invisible to an accelerometer.
Risk score calibration
Fitting weights against collision outcomes. A fleet's own accident record unblocks this; a carrier's claims data unblocks the insurance version of it. No amount of engineering substitutes for either.
Who this is for
- Commercial fleets running forward-facing cameras who want collision causes, not event counts.
- Telematics platforms and dashcam makers who want camera-derived signals without building the perception stack.
- Insurance carriers running usage-based programmes that have reached the limit of accelerometer data.