Top 50 Analog Neural Network Chip in Europe

The startup develops a neuromorphic chip that mimics human brain information-processing mechanisms to enhance artificial intelligence hardware. This technology addresses computing bottlenecks by enabling more efficient training of neural networks for AI applications.

Innatera provides ultra-low-power neuromorphic processors for edge AI applications. Their spiking neural processors enable real-time pattern recognition with sub-milliwatt power consumption and significantly reduced latency for battery-powered devices.

Mach42 utilizes proprietary neural network technology to accelerate the verification process of analog circuit designs, achieving high accuracy with minimal data input. This platform significantly reduces design cycle times, enabling faster time-to-market for complex simulations in engineering and scientific applications.

SynSense develops mixed-signal neuromorphic processors that achieve ultra-low power consumption and low-latency performance for edge computing applications. Their technology addresses the challenges of high energy use and slow response times in AI systems, enabling efficient real-time processing across various domains such as robotics, smart homes, and autonomous driving.

Agile Analog provides customizable, multi-process analog IP technology that enables semiconductor designers to create optimized, fab-ready analog components tailored to specific applications and foundry processes. This approach reduces the complexity and cost associated with traditional analog IP integration, allowing for greater control over the design flow and faster development cycles.

SpiNNcloud Systems develops specialized hardware that replicates brain-like parallel processing to enhance real-time computing for complex simulations and data analysis. This technology overcomes the limitations of traditional computing architectures, significantly improving efficiency in handling large-scale data tasks.

Salience Labs is developing a hybrid photonic-electronic chip designed to enhance the processing speed and energy efficiency of artificial intelligence applications. This technology addresses the limitations of traditional electronic chips by enabling faster data transfer and lower power consumption, crucial for scaling AI systems.

The startup develops a deep-tech semiconductor chipset that enhances data movement by bringing data processing closer to computation. This technology improves the execution speed of large language models while increasing data privacy and energy efficiency.

The startup develops neuro-sensing technology that facilitates direct communication between the human brain and artificial intelligence systems. This platform enhances user interaction with machines while improving the understanding of neurological disorders, enabling more intuitive and effective human-computer interfaces.

MintNeuro develops scalable semiconductor technology for next-generation neural implants that enhance the treatment of neurological conditions through compact, low-power solutions. The company aims to improve patient outcomes by enabling minimally invasive procedures that offer high performance and accessibility in medical interventions.

The startup develops ultra-low power AI solutions for edge devices, enabling real-time data processing without reliance on cloud infrastructure. This technology addresses the need for energy-efficient smart devices in environments with limited power availability.

Nuuron is a neurotech startup.

SEMRON develops a 3D-scalable AI inference chip using its proprietary CapRAM™ technology, which integrates compute-in-memory architecture to enhance energy efficiency and parameter density for AI applications. This technology addresses the high costs and power consumption of traditional AI chips, enabling efficient deployment of generative AI models directly on edge devices like smartphones and wearables.

Axoft develops a bioinspired neural implant that mimics the soft tissues of the brain, achieving a 1,000x greater electrode density than existing soft probes. This technology addresses the issues of implant drift and long-term damage, enabling precise, long-term communication with the nervous system at a single-neuron resolution.

Scalinx designs and industrializes high-performance semiconductor chips for analog signal conversion, featuring proprietary SCCORE™ technology that optimizes size, weight, and power consumption. Their solutions include highly configurable data converter cores and agile RF receivers, addressing the need for efficient, low-noise signal processing in communication, defense, and test measurement applications.

Alphawave Semi manufactures silicon IP and custom silicon solutions, including high-speed connectivity chiplets and subsystems, utilizing advanced technologies like 3nm UCIe™ and HBM3E. Their products address the need for reliable, low-latency interconnects in data centers, AI infrastructure, and 5G networks, enhancing performance and efficiency in high-demand computing environments.

Another Brain develops Organic AITM, a self-learning artificial intelligence inspired by the macroscopic functioning of the human brain, which operates efficiently without the need for large datasets. This technology enhances decision-making processes across various sensory modalities, providing a more human-friendly AI solution that is energy-efficient and capable of explaining its actions.

BIOS Health develops neural interfaces and AI technology to read and write neural data, enabling real-time analysis of the nervous system's signals. This approach addresses the malfunctioning signals that can lead to diseases, facilitating the creation of targeted pharmaceuticals and software-delivered therapies.

RaiderChip designs semiconductor hardware accelerators that enhance AI performance by addressing memory bandwidth limitations. Their solutions enable efficient AI inference for both edge and cloud applications, allowing users to run complex large language models locally with full privacy and without ongoing subscriptions.

NeuralAgent develops a decentralized AI-Operating System called Neural Cloud, which enables high-bandwidth connectivity and autonomous learning across space, airborne, and ground transport systems. This technology addresses the challenges of dynamic routing and data transfer for connected intelligence, significantly enhancing operational efficiency and reducing costs in telecommunications, defense, and mobility sectors.

INBRAIN Neuroelectronics develops graphene-based brain-computer interfaces (BCIs) that provide high-resolution, bi-directional neural decoding and modulation for patients with neurological disorders. Their technology addresses the limitations of current neuroelectronic therapies by offering a less invasive, personalized approach to restore function and mobility in conditions such as Parkinson's disease.

The startup offers a photonic computing platform designed to enable the development of artificial general intelligence (AGI) at scale. This technology addresses the limitations of traditional computing by providing a more efficient and sustainable infrastructure for complex AI computations.

The startup develops an optical interposer that utilizes light for energy-efficient die-to-die interconnects, enabling high-performance computing (HPC) processors to achieve full scalability with multi-chipset configurations. This technology addresses the limitations of traditional electrical interconnects, enhancing data transfer speeds while reducing power consumption.

Akhetonics is developing the world's first all-optical XPU, a general-purpose photonic processor that maintains data in the optical domain throughout processing, eliminating the latency associated with electronic signal conversion. This technology enables ultra-low power, high-performance computing and AI, addressing the limitations of traditional von Neumann architectures by integrating optical digital, analog, and quantum computing capabilities.

Symbionics is developing next-generation brain-computer interfaces that enable bidirectional communication between the human brain and machines, utilizing high-resolution neural signal acquisition and excellent biocompatibility. This technology aims to enhance neurological treatment options and improve human capabilities by facilitating seamless interaction with digital devices.

AOPTeam develops a universal neural network that processes raw sensor data to make real-time driving decisions in various environments. This technology enhances safety and reliability in autonomous driving, making it accessible and affordable for multiple industries.

Opteran develops neuromorphic software that mimics the brains of insects and animals, enabling autonomous machines to navigate complex environments without relying on GPS or extensive data collection. This technology provides robust and efficient localization in dynamic conditions, enhancing the operational capabilities of mobile robots in unstructured spaces.

Black Semiconductor utilizes graphene to create ultra-fast, energy-efficient chip networks that enable thousands of chips to communicate as a single unit. This technology addresses the limitations of traditional electronic connections by integrating photonics with electronics, enhancing data communication speed and scalability in the semiconductor and electronics industries.

HABS AI offers a Brainwaves As A Service (BaaS) platform that decodes EEG data using AI to generate a "Cognitive Persona." This platform extracts neurocognitive metrics like concentration and fatigue, enabling seamless integration of brainwave analysis into applications for healthcare, cybersecurity, and marketing.

Kalray offers high-performance processing acceleration solutions powered by its MPPA® architecture. These solutions efficiently handle data-intensive workloads in AI, automotive, and telecommunications, delivering superior performance and energy efficiency for demanding applications.

Intrinsic Semiconductor Technologies develops silicon-oxide based resistive random-access memory (RRAM) to provide efficient non-volatile memory directly integrated into advanced processor chips. This technology addresses the memory bottleneck in embedded systems, significantly reducing power consumption and costs while enhancing performance for microcontrollers and edge AI applications.

Axelera AI manufactures AI acceleration hardware, specifically the Metis AI Processing Unit (AIPU), designed for efficient edge computing with up to 214 TOPS performance and 15 TOPS per watt. The technology addresses the need for cost-effective and energy-efficient solutions in generative AI and computer vision applications across various industries, including retail and security.

The startup manufactures semiconductor chips with a multicore DSP architecture that accelerates the design of complex integrated circuits for mobile and network infrastructure. By eliminating the need for DSP coprocessors, these chips enable chipmakers to efficiently develop next-generation digital communication systems, including fifth-generation technologies.

Neuroelectrics develops a cloud-based platform that utilizes personalized transcranial electrical stimulation (tES) to target dysfunctional neural circuits associated with brain disorders such as depression and epilepsy. This non-invasive approach offers an alternative for patients whose conditions remain uncontrolled by traditional pharmacological or surgical treatments.

The startup develops biosensing technology that integrates electrodes into wireless earphones to monitor brain and facial activity. This enables audio device users to control their earphones through voiceless and touchless interactions, providing insights into user engagement and performance.

MaxWell Biosystems develops high-density microelectrode array platforms, MaxOne and MaxTwo, for high-throughput functional imaging of iPSC-derived cells, enabling detailed monitoring of neuronal activity and drug responses. Their technology addresses the need for precise safety pharmacology and toxicology assessments in preclinical drug discovery, facilitating faster and more reliable research outcomes.

Qilimanjaro develops application-specific analog quantum computing systems, utilizing superconducting circuits to address complex challenges in industries such as chemistry, finance, and logistics. Their technology enables faster simulations and optimizations, providing tailored solutions that enhance operational efficiency and reduce development complexity.

InstaDeep develops AI-powered decision-making systems utilizing GPU-accelerated computing, deep learning, and reinforcement learning to tackle complex challenges in industries such as logistics, energy, and biology. Their technology enhances operational efficiency and precision, enabling enterprises to make data-driven decisions in an increasingly AI-centric landscape.

PHOTON IP develops advanced optical chips utilizing innovative photonics technologies to enhance data transmission and processing capabilities. The startup addresses the limitations of current optical systems by providing high-performance solutions that improve efficiency and reduce energy consumption in various applications.

NETRI develops human cell-based assays and organs-on-chip technologies that utilize neurons as biosensors to evaluate acute and chronic responses in pharmaceutical research. By providing high-throughput electrophysiological recording and AI-driven predictive analytics, NETRI enhances drug discovery and preclinical testing across various therapeutic areas, including oncology and neurological disorders.

The startup develops a chip verification platform that utilizes an algorithm for electrically accurate, full-chip analysis at the transistor level. This technology reduces errors in semiconductor design, enhancing precision and efficiency during complex project workflows.

The startup develops Artificial Brain Intelligence (ABI) technology that integrates neuroscience principles with AI to enhance analytical accuracy across various industries. Its end-to-end ABI solutions address complex business challenges by providing precise time series analytics, enabling organizations to make data-driven decisions effectively.

Literal Labs develops AI models based on Tsetlin Machine algorithms, which provide ultra-low power consumption and up to 250 times faster inference compared to traditional neural networks. Their technology enables on-device training and explainable AI, addressing the need for energy-efficient and transparent solutions in edge computing applications.

The startup has developed a visual search platform that utilizes artificial intelligence and neural networks for rapid image and video recognition. This technology enables users to quickly locate products and objects within visual content, delivering results in under one second.

The startup develops medical software that utilizes artificial intelligence to analyze electroencephalography recordings, generating simplified parameters for clinical decision-making. This technology enhances patient care in intensive settings by improving the quality and cost-effectiveness of brain monitoring solutions.

Nanomation develops automation software that enhances the application of nanomaterials in chip manufacturing, enabling the production of faster and more efficient microchips without increasing transistor density. This technology addresses the limitations of traditional chipmaking methods as they approach physical density constraints, facilitating broader use of nanotechnology across various industries.

Neucom provides the ADA platform, a neuromorphic processing system that enables low-power, event-based computation for edge devices. Its Turing-complete architecture and user-friendly SDK allow developers to adapt complex algorithms, including post-quantum cryptography, for efficient implementation without prior spiking neural network expertise.

The startup develops neuromorphic algorithms and low-energy machine vision systems that utilize asynchronous event-based processing to enhance predictive decision-making. This technology enables clients to minimize reliance on large datasets, significantly lowering costs associated with AI deployment.