Our Process

We start by identifying critical safety requirements and Advanced Driver Assistance System (ADAS) functionalities for clients. This phase involves analysing the specific needs for Level 2 and Level 3 autonomous driving, ensuring that each feature aligns with DeepGrid’s vision of zero fatalities on roads.

Our design team develops the hardware architecture for the DGrid-SoC, focusing on power efficiency and performance. By leveraging Domain-Specific Architecture (DSA) and customised Domain-Specific Languages (DSLs) SDK Software, we optimise each hardware design to efficiently process high volumes of data from multiple sensors, including cameras, LIDAR, and radar.

The DGrid-SoC customised Hardware design is integrated with the vehicle's system to enable real-time sensor fusion. This integration allows for seamless data flow across key ADAS functions, such as object detection, edge recognition, and point-of-interest detection, which are essential for safe autonomous driving.

Before deployment, the DGrid-SoC customised Hardware design undergoes comprehensive testing through real-world simulations. This stage replicates diverse driving conditions to fine-tune the SoC's performance, ensuring robustness and reliability across various scenarios and road environments.

Our Dgrid-SoC integrates with Augmented Reality (AR) Heads-Up Display (HUD) to enhance the user experience. This feature provides real-time, on-screen updates on hazards, navigation, and adaptive driving information, helping drivers make informed decisions while maintaining energy efficiency.

With a planned launch in Jan 2025,, our DGrid-SoC is designed for market readiness as a high-performance, low-power solution for autonomous vehicles, particularly in the electric vehicle sector. This deployment phase represents our commitment to delivering transformative solutions in the ADAS and autonomous driving industry.