Fallstudie

MOTER & Sonatus—Driving Safety at the Edge

Transforming Insurtech with
In-Vehicle AI

This case study highlights how MOTER Technologies partnered with the Sonatus AI Director platform to embed advanced driver risk modeling directly within vehicles.

This collaboration enables a dynamic, personalized insurance model that moves beyond traditional factors like age or ZIP code to focus on real-world driving behavior.

Learn how MOTER and Sonatus are making connected vehicles safer and more insurable by design by:

    • Richer Data: Access to high-fidelity vehicle sensor data and non-traditional indicators like following distance and driver distraction.
    • Real-Time Coaching: Enables continuous risk assessment and personalized driver feedback without relying on constant cloud connectivity.
    • Security & Privacy: Uses containerized execution to protect proprietary algorithms and keeps sensitive behavioral data within the vehicle, aiding GDPR/CPRA compliance.
    • Cost Savings: Reduces data transmission and cloud processing costs for OEMs by executing models at the edge.
    • Scalability: Sonatus provides a unified, flexible deployment framework for rapid integration across diverse vehicle lines and ECU environments.

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Frequently Asked Questions

Traditional UBI relies on OBD dongles or smartphone apps, both of which have significant flaws. Dongles are costly, unreliable across different vehicle types, and can interfere with other systems. Smartphone apps often lack precision, struggle to distinguish between drivers and passengers, and face data reliability issues if users revoke permissions.

In contrast, MOTER’s solution is embedded directly into the vehicle’s operating system. It leverages high-fidelity sensor data to analyze not just driving mechanics (speed, braking) but also crucial contextual factors such as:
- Traffic conditions and signal states.
- Pedestrian presence and following distances.
- Driver distraction levels and lane-changing frequency.

The Sonatus AI Director is the technical enabler that allows MOTER’s advanced risk models to run directly on the vehicle's existing hardware ("the edge") rather than in the cloud. It solves critical integration challenges by providing:
- Secure Execution: A containerized runtime environment that protects MOTER’s proprietary algorithms and sensitive driver data.
- Standardized Access: A unified set of APIs that allows the software to easily access diverse vehicle data signals across different OEM platforms.
- Hardware Flexibility: The ability to deploy models across various ECU types without requiring costly custom integration for every new vehicle program.

By moving risk assessment from the cloud to the vehicle edge, OEMs unlock several strategic and operational advantages:
- New Revenue Streams: It creates opportunities for "differentiated insurance and fleet services," allowing OEMs to offer embedded insurance and advanced driver coaching directly to customers.
- Cost Reduction: Processing data locally significantly reduces the volume of telematics data that needs to be transmitted, lowering communication and cloud processing expenses.
- Regulatory Compliance: The "Privacy-By-Design" architecture keeps sensitive behavioral data inside the vehicle, simplifying compliance with strict regulations like GDPR and CPRA.
Rapid Scalability: The unified software framework allows OEMs to deploy these features across multiple vehicle lines in "days rather than months".

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