Infineon has acquired the Stockholm-based startup Imagimob AB, a leading platform provider for Machine Learning solutions for edge devices. With this acquisition Infineon advances its position to offer a world-class Machine Learning (ML) solution and significantly complements its AI offerings. Imagimob provides an end-to-end machine learning toolchain that is highly flexible and easy to use with a strong focus on delivering production-grade ML-models. Infineon is acquiring 100% of the company’s shares. Both parties have agreed not to disclose the amount of the transaction.
“Artificial Intelligence and ML respectively are about to largely enter every embedded application and thus enable new functionalities. With Imagimob’s outstanding platform and its expertise in developing robust machine learning solutions for edge devices, we further strengthen our ability to enable new levels of control and energy efficiency on our products while preserving privacy,” said Thomas Rosteck, President of Infineon’s Connected Secure Systems division. “We enable our customers to leverage the advantages from AI/ML and bring their products to market quickly by building on our advanced sensors and IoT solutions portfolio”.
”With Infineon we can accelerate our customer’s developments, enable new applications and help them to differentiate in their markets,” said Anders Hardebring, Co-Founder and CEO of Imagimob. “Becoming an integral part of the Infineon ecosystem with their profound application expertise and an extensive product portfolio allows us energy efficient and secure implementation of advanced sensing and control in IoT contexts”.
Imagimob is a leading player in the fast-growing market for Tiny ML and Automated Machine Learning (AutoML), providing an end-to-end development platform for ML on edge devices. Imagimob’s platform enables a wide range of use cases, such as audio event detection, voice control, predictive maintenance, gesture recognition, signal classification as well as material detection, and will extend Infineon’s hardware/software ecosystem even further. Applying the combined expertise to the complete range of sensors will provide existing customers of both companies a unified user experience across products, enable rapid deployment of robust solutions and accelerate the further adoption of Tiny Machine Learning through all applications and segments.
