True innovation in tiny machine learning (tinyML) emerges from a synergy between software ingenuity, real-world application insights and leading-edge processor IP. In this presentation, we will explore the process of integrating these elements to shape the design of our latest NPU IP—the Ceva-NeuPro-Nano. Through real-world use cases, we will examine how software architecture and detailed analysis of use cases were pivotal in guiding the NPU architecture design process, yielding a versatile and efficient single-core solution capable of handling control, digital signal processing and neural network inference tasks. Software is crucial in unlocking the potential of hardware and adapting to diverse application demands, and we will show how Ceva’s software innovations, harnessing the capabilities of leading neural network inferencing frameworks, ensure that Ceva-NeuPro-Nano is highly effective in practical scenarios. We will conclude by reviewing the exciting hardware and software extensibility features of NeuPro-Nano, which push the boundaries of customizability.