AIRS ML

The platform delivers edge‑deployed artificial intelligence that applies compressive sensing techniques to monitor assets in real time. It ingests data from existing sensors, runs containerized inference models on‑site, and generates predictions about imminent machine failures. By processing signals locally, it reduces latency and bandwidth requirements while providing continuous health diagnostics.

Target users are industrial operators and equipment manufacturers that need predictive maintenance for high‑value machinery, as well as electric‑vehicle infrastructure providers seeking to optimise charge‑point performance and battery thermal management. The software can be integrated with current sensor stacks and scaled across factories through its modular, container‑based architecture.

Distinctive aspects include a focus on edge AI for compressive sensing, a suite of components such as “AIRS Integrate” for data analysis and root‑cause detection, “AIRS Prophecy” for factory‑wide deployment with digital‑twin support, and specialised optimisation for EV charge points. The offering is currently in an experimental stage.