Our vision is to enable Physical AI — intelligent inference embedded in the real world, operating without reliance on the Internet or the cloud.

We enable Physical AI through tiny, programmable, ultra-low-power AI chips embedded at or near the sensor level. These chips perform real-time inference locally, allowing devices such as motors, engines, robots, drones, AR/VR glasses, and medical systems to sense, interpret, and respond—without reliance on cloud connectivity.

Our mission is to drive the “Distributed Intelligence” paradigm by delivering software-configurable AI inference chips and end-to-end solutions that combine low power, low latency, and inherent privacy for real-world sensing applications.

Founded in 2020 by veteran Silicon Valley engineers, Ai Linear is built on a portfolio of over 35 U.S. patents covering key building blocks for analog and mixed-mode machine learning. Our proprietary algorithms and software enable efficient, domain-specific inference engines operating directly on or near sensors, eliminating the need for continuous data transmission or cloud-based processing.

We design programmable system-on-chip solutions that integrate analog, digital, and algorithmic intelligence to extract meaningful insights from sound, vibration, wave, and image signals—often performing inference before data is digitized or transmitted.

While cloud-based training remains essential, the next frontier is executing intelligence in the physical world through localized inference. By transforming low-cost sensors into intelligent, energy-efficient systems, we enable scalable, secure, and real-time operation across industries.