With the rapid evolution of computing technologies, especially in the era of Industrial IoT (IIoT) and AI-driven applications, device manufacturers are under increasing pressure to deliver scalable, high-performance solutions across a wide range of product tiers. This is particularly challenging for companies developing both high-end and entry-level systems, as they must integrate diverse and often complex technologies while maintaining efficiency and competitiveness.

Adopting a System-on-Module (SOM) architecture offers a robust and future-ready approach to meet these demands. SOM modules abstract the complexities of CPU and system-level design, allowing developers to focus on application-specific customization via carrier boards. This modularity is especially valuable in Industrial IoT and AI applications, where edge computing devices require optimized performance, reliability, and adaptability for real-time data processing, machine learning inference, and sensor integration.

By leveraging industry-standard commercial off-the-shelf (COTS) SOM solutions, OEMs can accelerate development timelines, reduce R&D costs, and ensure a streamlined path to market. Moreover, this approach enables easier scalability and product longevity—critical factors in industrial and AI-driven environments where upgrade cycles and interoperability are key.