On-board Artificial Intelligence (AI) is rapidly becoming central to modern satellite operations, enabling real-time decision-making, advanced data processing, and greater autonomy. By reducing dependence on ground stations, AI enhances mission efficiency through faster Earth observation insights, improved fault detection, optimized resource usage, and more effective collision avoidance. As space systems increase in complexity, AI accelerators play a critical role in achieving these capabilities. However, ensuring standards compliance for AI accelerators in European space missions presents unique challenges. Unlike conventional infrastructure components governed by established standards, AI systems lack clear functional requirements and traceability frameworks, especially when developed iteratively. This places a greater burden on companies to define and justify their methodologies, increasing the cost and complexity of certification. In 2022, the authors introduced a novel on-board AI software approach based on high-throughput, low-power data pipelines optimized for space-grade high-performance computing. Building on this foundation, the 2024 European Space Agency (ESA)-funded PATTERN project—conducted in collaboration with Frontgrade Gaisler—extends Klepsydra AI’s support to a wider range of space-qualified processors and platforms, including LEON4, LEON5, NOEL-V (RISC-V), and Microchip’s PolarFire, all running RTEMS6 SMP (Real Time Operating System with Symmetric Multiprocessing support). This work also establishes a path toward compliance with the European Cooperation for Space Standardization (ECSS) standards ECSS-E-ST-40 and ECSS-Q-ST-80 software standards. Through the ESA MANDALA project, Klepsydra and ZHAW University further demonstrated AI execution on the HPDPv1 hardware accelerator. Together, these projects represent a major European milestone toward deploying high-performance, safety-compliant AI in radiation-hardened, space-qualified environments.