Matta

About Matta

Matta is an industrial AI company that develops manufacturing foundation models and a general-purpose manufacturing platform to enhance factory operations. The company was founded in 2019 as a spin-out from the University of Cambridge's Institute for Manufacturing (IfM) by Douglas Brion (CEO) and Sebastian Pattinson (CSO). Brion holds a PhD in deep learning-enabled control, while Pattinson is an Associate Professor of Engineering and leader of the IfM's Computer-Aided Manufacturing group. The founding team combines experience from institutions like MIT, Google X, and Microsoft. Matta has raised $15.7 million in total funding, including a $14 million seed round led by Lakestar with participation from Giant Ventures, InMotion Ventures, and others. The company's core offering is a full-stack, plug-and-play system that integrates hardware, software, and advanced AI models. This system uses unsupervised and self-supervised computer vision to give factories the ability to monitor, understand, and improve their processes in real-time. Its primary functions include automating quality control, detecting anomalies and defects, performing measurements, diagnosing root causes, and recommending corrective actions. The technology is designed for rapid deployment, often going live within hours, and can achieve high accuracy with minimal training data. For instance, in one polymer manufacturing application, the system reached over 99% defect-detection accuracy with only ten minutes of data. The platform is highly adaptable, serving a wide range of industries from electronics and automotive to defense and apparel. Matta employs a dual commercial strategy: selling its retrofittable system directly to manufacturers and partnering with Original Equipment Manufacturers (OEMs) to embed its AI into new machinery. This allows the technology to be integrated with manual inspection stations, conveyor lines, and robotic arms. By capturing and scaling tacit operational knowledge, Matta aims to reduce waste, boost productivity, and enable the development of fully autonomous, end-to-end production systems.