Sonatus unveiled Sonatus AI Director, a revolutionary platform that lets OEMs use AI at the vehicle edge. By 2034*, the automotive AI market is expected to grow to a size of $46 billion annually, with in-vehicle edge AI software and services playing a bigger role.
Sonatus AI Director satisfies this need by offering OEMs and suppliers an end-to-end toolchain for training, validating, optimizing, and deploying models. It also integrates with vehicle data seamlessly, runs models in isolated environments, and offers cloud-based remote model performance monitoring.
Compared to today’s fragmented approach employing several ML development (MLops) tools, Sonatus AI Director’s full toolchain and in-vehicle runtime environment reduces the hurdles to edge AI adoption and innovation, cutting down on effort from months to weeks or days.
Throughout the lifecycle of passenger and commercial vehicles, OEMs are constantly looking for new and creative methods to provide value to their customers. With the use of in-vehicle edge AI powered by contextual and real-time vehicle data, OEMs may unleash new features and capabilities that facilitate preventive maintenance, enhanced efficiency, optimal vehicle performance, and adaptive and personalized driving experiences.
Sonatus AI Director enables automakers to implement AI directly in the car rather than depending only on cloud-based models.
This results in quicker reaction times, lower data upload costs, data and algorithm privacy, and continuity even in the event of intermittent connectivity.
OEMs may utilize Sonatus AI Director to optimize their current compute resources instead of waiting for next-generation ECU hardware, which will speed time-to-market and give them a way to scale AI performance when new silicon becomes available.
To meet the needs of various vehicle use cases, Sonatus AI Director offers a variety of model types, such as those based on physics, neural networks, and Small and Large Language Models (SLMs/LLMs).
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.
Key issues facing the industry in implementing in-vehicle edge AI are resolved by the Sonatus AI Director:
- 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.
Successful in-vehicle edge AI is enabled by the capabilities of software-defined vehicles. Sonatus has a proven track record of delivering key SDV building blocks covering everything from the cloud to the vehicle edge, including on-demand access to precise vehicle data, a critical foundational element in this new innovation.
Existing products, such as Sonatus Collector AI and Sonatus Automator AI, can complement Sonatus AI Director; the combination further extends the capabilities of each. Similarly, models managed by Sonatus AI Director can enhance the capabilities of Sonatus AI Technician, such as building in detectors for various types of anomalies that may assist with vehicle diagnostics.
Sonatus will demonstrate Sonatus AI Director publicly for the first time at the IAA Mobility conference in Munich, Germany, September 8-12, 2025. For more details, visit the Sonatus AI Director web page or the solution brief “Deliver In-Vehicle Edge AI at Scale” that includes more details about representative use cases.
Leadership Comments
“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.”
“The evolving technology and competitive landscape are compelling automakers to transition towards software-defined vehicles and make greater use of AI to improve their business,” said Alex Oyler, consulting director at global automotive research firm SBD Automotive. “Innovative tools like Sonatus AI Director can expand the use of in-vehicle AI to deliver adaptive, intelligent, and compelling driving experiences that ensure OEMs stay ahead of global competition.”
