Reynolds & Moore helps teams move AI-enabled systems from prototype to certification-ready deployment by embedding functional safety engineering early in the development lifecycle. Our work within the NVIDIA Halos AI Systems Inspection Lab ecosystem allows our engineers to contribute to safety design and certification strategies for edge AI systems while building practical experience with e.g., NVIDIA IGX Thor and its safety capabilities. By adapting the V-model framework for AI-driven systems, we reduce integration risk and support safer, more predictable system behavior as teams prepare for certification and compliance.

​​As an ecosystem member, Reynolds & Moore works within the NVIDIA Halos AI Systems Inspection Lab, the first ANSI National Accreditation Board (ANAB) accredited inspection lab for AI-driven physical systems. NVIDIA Halos is a comprehensive full‑stack safety system for physical AI that unifies safety elements across vehicle and robotics architectures and their underlying AI models. It combines hardware and software components, tools, models, and design principles to safeguard AI‑based, end‑to‑end AV and robotics stacks.​

Certifying AI-driven robotics systems is challenging. Traditional compute platforms do not include safety features, so engineers must add external controllers, monitoring tools, and redundant systems. This results in complexity, increases integration risk, and lengthens the verification process. As a solution, we streamline these processes by implementing safety strategies and system frameworks that incorporate technologies to enable deterministic behavior and real-time decision-making in safety-critical applications.

One of the key features of the NVIDIA IGX Thor platform is its integrated Safety Island, a dedicated microcontroller that operates independently from the main processor. It keeps crucial safety operations active even if the primary system fails. This built-in capability can support certification efforts and reduces reliance on additional safety hardware, making it especially valuable for functional safety engineers.

Choosing the right compute platform from the beginning is a strategic safety decision. Platforms that natively support safety-critical functions reduce the need for multiple external safety controllers and complex redundant architectures. This simplification lowers hardware costs, reduces integration risk, and creates a cleaner safety architecture. As a result, certification activities become more structured and predictable, development timelines shorten, and long-term maintenance is easier to manage, all of which are critical advantages in safety-critical deployments.

• Research & Development: Focusing on safety feature development, safety framework implementation, and test methodologies to drive innovation and reliability
• Safety Concept & Strategy: Performing a gap analysis, hazard analysis & risk assessment, functional safety concept, and maintaining functional safety management as the foundation for safety planning
• System Design & Development: Defining safety requirements, safety architecture, component selection, and conducting reliability analysis to shape the system’s technical integrity
• Testing & Validation: Conducting failure modes and effects analysis, test planning and execution, and prototype field evaluations to validate performance and safety
• Safety Case & Certification: Creating new safety cases, technical construction files, and third-party certification support to meet industry safety requirements
• Compliance & Support: Conducting regulatory compliance strategy, marking assistance, and documentation management for regulatory alignment