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Fastlane™ Edge
In-Vehicle AI at Scale
Deploy, orchestrate, and manage AI models, diagnostic logic, and vehicle intelligence at the edge to accelerate development, enhance quality, and continuously improve vehicles throughout their lifecycle.
Operationalize Vehicle Intelligence
Deploy AI models, diagnostic logic, and software-defined intelligence into production vehicles at scale.
Optimize in-vehicle AI execution
Maximize performance across vehicle compute resources while minimizing integration effort, hardware dependencies, and operational complexity.
Enable smart vehicle capabilities
Continuously monitor vehicle behavior and execute intelligence at the edge to detect anomalies, support self-diagnosis, and improve vehicle performance over time.
Fastlane Edge operationalizes vehicle intelligence by deploying AI models, virtual sensors, and diagnostic logic directly within the vehicle.
Streamlined Edge AI deployment
Deploy AI models, diagnostic logic, virtual sensors, and predictive analytics into production vehicles.
- Unified deployment and runtime environment
- Fleet-wide rollout management
- OTA deployment and updates
- Runtime lifecycle management
- Versioning and governance
- Cloud-to-vehicle orchestration
- Multi-platform ECU support
Edge AI Optimization
Run intelligent workloads efficiently across diverse vehicle architectures and compute platforms.
- CPU, GPU, and NPU support
- Hardware-aware AI optimization
- Resource-aware scheduling
- Runtime adaptation to ECU capabilities
- Silicon vendor integrations
- Cross-platform portability
- Power and thermal optimization
- Efficient use of existing vehicle hardware
Adaptive Vehicle Features
Turn vehicle intelligence into real-time actions that improve quality, reliability, and performance.
- Real-time anomaly detection
- Predictive maintenance monitoring
- Self-diagnostic workflows
- Virtual sensor execution
- Adaptive monitoring and alerting
- Software-defined vehicle features
- Context-aware decision making
- Edge-based quality detection
Fleet-Wide Intelligence
Transform successful anomaly detectors, diagnostic logic, and predictive models into fleet-wide capabilities that continuously improve vehicle quality and performance.
- Fleet-wide Over-the-air (OTA) model distribution
- Model lifecycle management
- Versioning and governance
- Fleet-wide AI performance monitoring
- Edge-to-cloud feedback integration
- Reusable AI model and intelligence libraries
Related resources
COMPREDICT Unlocks Smarter Headlight Leveling with Sonatus AI
COMPREDICT, in partnership with Sonatus, has developed an AI-based Virtual Headlight Leveling Sensor to meet the 2027 UN R48-09 regulation, replacing costly traditional sensors. This software-only solution utilizes CAN signals and the Sonatus AI Director platform to deliver accurate, real-time headlight leveling across various vehicle platforms, reducing hardware costs by up to $20 per vehicle.
Michelin and Sonatus – Intelligent Tire Maintenance and Performance
Enabling Real-Time Tire Intelligence through Embedded AI and Physics models. Traditional tire monitoring relies on basic pressure and temperature data, failing to capture real-world driving conditions. Because of this blind spot, tires are often driven unsafely with undetected wear, or replaced far too early—with only 14% actually reaching their true end of life.
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.
FAQ
Driver app platforms are an important component of vehicle infrastructure, but are not able to deliver the capabilities provided by Fastlane Edge. Many in-vehicle AI applications require access to vehicle data sources and other capabilities that aren’t exposed through the driver console or IVI subsystem. In fact, Fastlane Edge is an ideal complement to existing driver apps, enabling notifications powered by data sources and deep vehicle analytics that driver apps can’t access.
No. An important benefit of Fastlane Edge is that it takes advantage of the compute capabilities already available in the vehicle. A significant number of value-creating edge AI workloads do not require high-performance compute resources. In many cases, existing vehicle compute is more than enough to allow valuable insights to be created without requiring upgrades to expensive AI or GPU solutions. Of course, if high-performance solutions are available, they can be used as well.
Yes. Fastlane Edge is also designed for commercial vehicles, supporting in-vehicle intelligence, diagnostics, and edge AI workloads that are especially valuable for commercial vehicles. Fastlane Edge enables deployment of AI models for use cases such as after-treatment system management, ADAS, and other mission-critical functions. Fastlane Edge also supports vocational applications across industries including construction, agriculture, mining, and other off-highway vehicles.
No. Fastlane Edge does not provide autonomous driving or advanced driver assistance systems (ADAS) features. What it does offer is high-quality access to vehicle data and analytics that can support the development, tuning, and validation of ADAS systems. Fastlane Edge helps teams work with richer, multi-sensor data, but the ADAS and autonomous capabilities themselves are delivered by other companies.
Fastlane Edge builds upon the earlier innovations from Sonatus AI Director, and takes them further by tightly coupling the solution with the other products in Fastlane Platform to provide a critical step in the Observe-Analyze-Act loop. Fastlane Edge, together with Fastlane Insight, allows flexible, agentic deployment of AI models into the vehicle for deeper analytics, diagnostics, and upgradable capabilities.
As the third component of the Observe-Analyze-Act loop, Fastlane Edge is taking the place of these prior solutions and enhances them with the ability to take action within the vehicle, from updating individual vehicle settings to deploying new software and/or taking other actions in the vehicle. Fastlane Edge will continue to develop rich capabilities over time to further enhance the ability to take action based on an OEM’s desired capabilities.