Neuronova is tackling one of the central constraints of edge AI: power. Running capable AI on small, battery-powered devices is hard because conventional processors consume too much energy. Neuronova's answer is neuromorphic computing, a brain-inspired chip architecture designed to deliver high AI performance at a tiny fraction of the power, making it feasible to run meaningful intelligence directly on wearables, sensors, and other IoT devices without constant cloud connectivity.
The Milan-based startup was founded in 2024 by three PhD engineers in neuromorphic computing, Alessandro Milozzi, Michele Mastella, and Marco Rasetto, whose research has appeared in leading journals including Nature and who bring industrial experience alongside support from Politecnico di Milano. Their core technology is an ultra-low-power processor that the team says can reduce power consumption by orders of magnitude compared with traditional approaches, opening the door to always-on AI in devices where battery life is a hard limit.
The market implications are significant. As AI moves toward the edge for reasons of latency, privacy, and cost, demand grows for silicon that can run models locally on constrained hardware. Neuronova targets smart devices and sensors, a category spanning consumer wearables, industrial monitoring, and embedded systems, where its energy efficiency could unlock applications that are impractical with today's chips.
Neuronova raised a €1.5 million pre-seed round in late 2024, led by 360 Capital alongside Tech4Planet and CDP Venture Capital. As an early-stage deep-tech company, Neuronova faces a long and capital-intensive path from research-grade processor to commercial silicon, and competes in a neuromorphic field that has seen many ambitious efforts. But the founding team's academic depth, the structural shift toward edge AI, and a sustainability angle tied to dramatically lower energy use give Neuronova a credible thesis in the increasingly important low-power AI hardware segment.