Accurate, real-time crash detection that accelerates claims and reduces uncertainty.
We detect, validate, and contextualise vehicle crashes instantly—delivering trusted FNOL signals insurers can act on with confidence.
Traditional FNOL relies on delayed customer reporting and incomplete information. Our crash detection layer removes that dependency by identifying impact events automatically, in real time.
We combine accelerometer data, trip context, and behavioural signals to determine whether a genuine crash has occurred—then enrich each event with severity indicators, confidence scores, and supporting data insurers need to respond quickly and accurately.
Immediate identification of impact events using high-resolution sensor data.
Each event is scored to indicate impact magnitude and likelihood of a genuine crash.
Multi-axis accelerometer data captures the dynamics of each incident.
Contextual filters remove harsh braking, potholes, and non-collision events.
High-severity crashes can be manually reviewed to confirm validity.
Crash data is delivered in formats ready for claims and triage workflows.
Sensor data identifies abnormal force patterns consistent with a collision.
Algorithms assess severity, direction, and context to confirm authenticity.
Crash details are enriched with speed, location, trip data, and timestamps.
Validated crash events are delivered instantly via API or secure feeds.
Answers to common questions about crash detection and FNOL delivery.
Crash events are detected and processed in real time.
We combine sensor data with contextual validation and optional human review.
Severity, confidence score, G-forces, speed, location, and trip context.
Yes. Events are delivered via APIs or customised data feeds.
No. It’s optional and typically reserved for high-severity events.
Yes. The platform is device-agnostic and supports multiple hardware types.
