With high-realism simulations, advanced digital human models, and expressive humanoid robots, we support the next generation of trustworthy in-cabin perception AI systems through data-driven methodologies.
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Best Practice
Accelerate AI development for autonomous driving
Perception models serve as the intelligence behind autonomous vehicles. Our approach enables both the generation of training data via simulation and the risk-free validation of these models in series production vehicles – significantly accelerating product maturity.
Precise perception as the key to autonomous mobility
For a vehicle to navigate autonomously, it must first understand its environment – identifying pedestrians, vehicles, and interpreting complex traffic scenarios. While powerful sensors are essential, it’s the highly specialized AI perception models that transform raw sensor data into meaningful insights. These models detect and classify objects, estimate distances, and provide the foundation for safe decision-making on the road. To ensure their reliability, perception models must be validated under real-world conditions such as rain, glare, construction zones, or heavy traffic.
However, traditional validation methods are complex, costly, and often risky. They require dedicated test fleets, intricate data pipelines, and labor-intensive evaluation processes across multiple systems. More critically, testing immature models in uncontrolled environments can pose safety risks, for instance, when misclassifications lead to incorrect vehicle behavior. In addition, GDPR-compliant data handling is a bottleneck. These challenges significantly slow down development, drive up costs, and hinder the advancement of autonomous driving technologies.
Streamlined, closed-loop development for reliable perception AI
Autonomous Reply and Storm Reply are meeting this challenge with a continuous, closed development cycle that empowers automotive manufacturers to bring perception models to the road faster, safer, and more efficiently. It integrates data collection, AI training, automated deployment, and real-world validation within a seamless cloud environment, enabling fully automated workflows, no media breaks, and real-time availability of insights and updates in a centralized system.
At the core of this approach is the innovative “shadow mode”. This capability allows new AI models to run in parallel with production software on series vehicles - enabling safe, real-world testing without impacting the operational driving system. The system autonomously compares multiple model versions directly on in-vehicle edge hardware, evaluates performance and stability, and continuously feeds insights back into the central platform. This accelerates model maturity and ensures rapid, measurable progress.
Additionally, the approach enables the targeted simulation of rare or edge-case scenarios that are unlikely to occur during standard road testing with GenAI. This enhances the robustness of perception models and further strengthens safety.
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Faster progress towards fully autonomous driving
Level 2 autonomous vehicles featuring semi-automated functions such as adaptive cruise control and lane keeping are already a part of everyday driving. The question is no longer if full automation will arrive, but when and who will lead the way. With our approach, you can accelerate the development of new autonomous functions while gaining a decisive competitive edge on the road to fully automated driving.
Testing on production vehicles, not in the lab
Validate perception models under real-world conditions: from night-time driving to complex urban traffic. This approach not only accelerates validation but also ensures the highest accuracy and relevance of collected data.
Clear comparability
Shadow mode enables multiple model versions to run in parallel, providing precise insights into object recognition quality and system response without compromising vehicle safety.
Accelerated development cycles
Seamless, end-to-end data and model processing reduces the time from implementation to validation from weeks to days. This enables faster iteration, shorter time-to-market, and more agile development workflows.
Optimized resource utilization & cost reduction
Eliminate the need for dedicated test fleets. Production vehicles become a scalable, cost-effective platform for training and evaluating new models - maximizing ROI and minimizing operational overhead.
Cloud & edge read
The OneLoop approach integrates effortlessly with leading cloud platforms such as AWS, Azure, and others. It fits smoothly into your existing toolchains and data pipelines, ensuring maximum flexibility, global scalability, and enterprise-grade compatibility.
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Within the Reply Group, Autonomous Reply is the specialised company for the software and system integration of autonomous things. The experts advise companies in the industrial, automotive and new mobility sectors from the sensor to the infrastructure. The portfolio includes holistic solutions across the entire value chain – from strategy definition and advice on application possibilities to design and implementation. The offer includes edge computing, embedded software, cloud services and integration into different eco-systems. State-of-the-art technologies and methods from the fields of deep learning, machine learning and computer vision are used.
Storm Reply is specialized in the design and implementation of innovative Cloud-based solutions and services. Through consolidated expertise in the creation and management of Infrastructure as a Service (IaaS), Software as a Service (SaaS), and Platform as a Service (PaaS) Cloud solutions, Storm Reply supports important companies in Europe and all over the world in the implementation of Cloud-based systems and applications. Storm Reply is AWS Premier Consulting Partner.