This is interesting. No mention of BRN but they have partnered with ARM and RENASES to name a couple
Sonatus Automator lets OEMs make automotive software updates that instantly create new vehicle functions and streamline vehicle testing and diagnostics.
www.sonatus.com
Extract only :-
Sonatus AI Director Unveiled to Power In-Vehicle Edge AI at Scale
New Sonatus platform helps OEMs use AI to transform driving and ownership experiences with greater efficiency and lower costs.
Sunnyvale, Calif., September 3, 2025 – Sonatus, a leading supplier of AI and software-defined vehicle (SDV) solutions, today announced Sonatus AI Director, a game-changing platform that enables OEMs to deploy AI at the vehicle edge. Automotive AI is growing rapidly, projected to reach a market size of $46B annually by 2034*, and in-vehicle edge AI software and services will be an increasingly important component. To meet this demand,
Sonatus AI Director provides OEMs and suppliers with an end-to-end toolchain for model training, validation, optimization, and deployment, while seamlessly integrating with vehicle data, executing models in isolated environments, and providing cloud-based remote monitoring of model performance. As a comprehensive toolchain and in-vehicle runtime environment, Sonatus AI Director lowers the barriers to edge AI adoption and innovation compared to today’s siloed approach using disparate ML development (MLops) tools, reducing effort from months to weeks or days.
OEMs are always seeking innovative ways to deliver customer value across passenger and commercial vehicles throughout their lifecycle. In-vehicle edge AI, fueled by real-time and contextual vehicle data, allows OEMs to unlock new features and capabilities that enable adaptive and personalized driving experiences, proactive maintenance, improved efficiency, and optimal vehicle performance. Instead of relying solely on cloud-based models, Sonatus AI Director lets vehicle manufacturers run AI directly in the vehicle, providing faster response, reducing data upload costs, preserving data and algorithm privacy, and ensuring continuity across intermittent connectivity. Rather than waiting for next-generation ECU hardware, OEMs can use Sonatus AI Director to maximize the value of their existing compute resources, accelerating time-to-market while also providing a path to scale AI performance as new silicon becomes available. Sonatus AI Director supports a range of model types, including physics- and neural network-based models, as well as Small and Large Language Models (SLMs/LLMs), catering to diverse vehicle use cases.
Sonatus AI Director solves key challenges the industry faces in deploying in-vehicle edge AI:
- Vehicle manufacturers (OEMs) gain a consistent framework that enables them to deploy models from different vendors with a single platform and across vehicle models.
- Tier-1 suppliers can optimize the systems they deliver to OEMs and more easily leverage AI across hardware and software technologies.
- Silicon providers can help their customers take full advantage of the compute and AI acceleration capabilities their chips offer.
- Suppliers and AI model vendors gain access to the needed input data from across different subsystems while protecting the intellectual property of their models.
“Artificial intelligence is creating opportunities for new ideas that were never before possible in vehicles,” said Jeff Chou, CEO and co-founder of Sonatus. “With Sonatus AI Director, we are empowering OEMs to deploy AI algorithms of all types into vehicles easily and efficiently, unlocking new categories and opening up an ecosystem of innovation that connects cloud, silicon, Tier-1 suppliers, and AI model developers.”
Using Sonatus AI Director, an OEM can easily manage and deploy a diverse set of AI models spanning many vehicle subsystems, realizing benefits that include cost, performance, security, and efficiency improvements. Initial launch partners include leading automotive silicon provider
NXP, compute IP leader
Arm, cloud service provider leader
AWS, and a range of subsystem expert model providers:
COMPREDICT, Qnovo, Smart Eye, and
VicOne. The model vendor launch partners have seen these benefits in their respective use cases:
- COMPREDICT AI-based Virtual Headlight Leveling Sensor reduces bill of materials (BOM) cost by up to $20 per vehicle by eliminating hardware components. COMPREDICT’s solution empowers OEMs to achieve full 2027 UN R48 compliance with a 100% software approach. The solution is part of COMPREDICT’s broader portfolio of embedded Virtual Sensors for the chassis and powertrain domains, enabling OEMs to reduce costs at scale, boost aftersales revenue, and unlock software-defined sensing easily across vehicle platforms.
- Qnovo Health & Safety Diagnostics (HSD) delivers 98.7% accurate battery fault prediction through multi-metric diagnostics. Integrated with Sonatus’s platform, AI-powered HSD enables deployment anywhere in the vehicle or cloud in a matter of days, creating a battery management solution that adapts to specific vehicles, drivers, and environmental conditions.
- SmartEye cabin monitoring systems can detect distracted drivers with very high accuracy. OEMs apply fixed rules to these detections to determine when to play in-vehicle alerts. With Sonatus AI Director, OEMs can more easily customize these alerts based on holistic driver behavior by combining distraction model outputs with data from other vehicle subsystems.
- VicOne xCarbon Edge AI, a GenAI-based in-vehicle intrusion detection system, enhances threat detection coverage from a single ECU to the entire vehicle. By sending only critical security events to the cloud, it can reduce data transfer and cloud processing costs by up to 60%. With dynamic model scheduling and various in-vehicle data collected by Sonatus AI Director, the system can accurately infer security risks and run compute-intensive AI models even on deployed hardware.
- Sonatus is demonstrating an engine anomaly detection model that can help vehicle engineers find suspicious timestamps without sifting through vast amounts of data while saving associated data upload costs by more than 6X when compared with running the model in the cloud.
www.nasa-beyond-challenge.org
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Why it’s probably fake:
Bottom line:
