Delft, 25 November 2020: The pioneering Dutch neuromorphic processor company Innatera Nanosystems has raised €5M in seed funding to bring its revolutionary brain-inspired processing technology to sensors and sensor-based devices. Innatera’s neuromorphic processing chip closely mimics the brain’s mechanisms for pattern recognition, enabling sensor data to be processed 100x faster and with up to 500x lesser energy than with conventional processors. These radical efficiency and performance gains allow advanced AI to be embedded into the sensor-edge, unlocking a wide gamut of applications including intelligent speech processing in human-machine interfaces, vitals monitoring in wearable devices, target recognition in Radars and Lidars, and fault detection in industrial and automotive equipment. Innatera is a spin-off of the renowned Delft University of Technology in the Netherlands.

Innatera’s management team (clockwise from left): Dr. Amir Zjajo (CSO), Dr. Rene van Leuken (Chief Advisor), Dr. Sumeet Kumar (CEO), Uma Mahesh (COO)

Innatera’s neuromorphic processor chip is radically different to the traditional AI chips being proposed by its competitors, and fundamentally changes how sensor data is processed. The technology relies on a new breed of analog-mixed signal computing circuits that recreate the behaviour of the brain’s fundamental building blocks – spiking neurons and synapses. Neural networks built with spiking neurons possess a precise notion of time which enables them to be a factor of 10-100x more compact than conventional artificial neural networks, especially for applications involving data with high spatial and temporal correlations. As a result of this approach, Innatera’s architecture delivers an unprecedented combination of ultra-low power and ultra-short recognition latency, with up to 10,000x higher performance per watt than typical digital processors and conventional AI accelerators.

Edge computing is gaining traction across domains including consumer electronics, IoT, smart industry, and automotive. IDC forecasts the edge AI processor market to reach the US$ 40B revenue mark by 2023. The market is expected to grow with a CAGR of over 85% as vendors integrate more AI-driven functionalities closer to sensors due to requirements for lower latency, communication cost constraints, and concerns over data privacy. A significant portion of the projected growth in this space is expected to come from always-on sensing applications that involve continuous monitoring of sensor data, and thus require energy-efficient processor chips that fit within the device. This is where Innatera finds that conventional processors and even other emerging accelerators fall short.

CEO Dr. Sumeet Kumar says: “The most impactful sensor-driven applications today are limited by the efficiency and speed of the processor, and this is more so in small, battery-powered devices than anywhere else. Innatera is reinventing processing for sensors by combining the energy efficiency of analog-mixed signal neuromorphic silicon with the performance gains of true spiking neural network algorithms, in a single integrated compute solution.”

Innatera has been working together with a number of big international names on applications that it suggests are game changers. The company expects these developments to surface in the consumer, industrial, and automotive markets in the next few years

The €5m seed investment round was led by Munich-based deep-tech investors MIG Verwaltungs AG and the Industrial Technologies Fund of btov. According to Dr. Christian Reitberger, Partner at btov, “Innatera sets itself apart from the plethora of AI accelerator companies by focussing on the edge of the edge – sensory data processing in the field. Translating truly brain inspired design principles into state of the art analog-mixed signal solutions enables a performance envelope not accessible to more conventional solutions”. Dr. Sören Hein, Partner at MIG added: “We were particularly impressed by the team which combines deep academic credentials with practical industry experience at leading semiconductor companies. They realized early on the fundamental importance of algorithms and software to unlock the market potential of SNN chips”.

Innatera is developing a suite of proprietary algorithms and an extensive software toolchain to realize the full potential of its neuromorphic silicon. The investment will enable the company to scale up its R&D efforts and accelerate product development to deliver on customer commitments through 2021. The company is hiring aggressively to support its ambitious roadmap.

About Innatera Nanosystems

Innatera is a trailblazing developer of ultra-low power neuromorphic processors for AI at the sensor-edge. The fast-growing company currently has about 15 employees at its headquarters in Delft, and is in the process of setting up a design center in Bangalore, India. Incorporated in 2018 as a spin-off from the Delft University of Technology, the company builds on over a decade of research into computational neuroscience and low-power processing.

About btov Partners

btov Partners is a pan European investment platform operating a Digital Technologies and an Industrial Technologies Fund complemented by a Private Investor Network of over 250 experienced business angels. With offices in Berlin, Munich, St. Gallen and Luxembourg, the company manages assets of more than EUR 500 million. The btov Industrial Technologies Fund is advised by a Munich based investment team and is focusing on the full industrial deeptech stack from hardware components to software, covering technology verticals from electronics, photonics, industrial IoT and quantum technologies to additive manufacturing and supply chain management. More information at

About MIG

MIG is a leading Germany-based venture capital firm with more than EUR 1 billion under management. MIG invests in deeptech, life science and digital health companies with a focus on early-stage teams with global ambitions. The MIG partners are all entrepreneurs who actively support the development of portfolio companies. For additional information, visit

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