Top 50 Analog Neural Network Chip in Asia

The startup specializes in neuromorphic analog signal processing technology to create ultra-low power AI chips that operate at microwatt levels and microsecond latency. This enables industrial electronics manufacturers to implement neural networks directly at the sensor, effectively addressing the challenges of power constraints in tiny AI applications.

CogniFiber provides anomaly detection services for industrial IoT, cybersecurity, and fintech using photonics technology, achieving 100 times faster processing at half the cost. This solution enables organizations to identify and respond to irregularities in real-time, enhancing operational efficiency and security.

SimChip specializes in the design and production of high-end analog integrated circuits, focusing on precision and performance for various applications. The company addresses the need for reliable and efficient analog solutions in industries such as telecommunications and automotive, enhancing signal integrity and reducing power consumption.

Develops on-device AI semiconductor solutions, including custom NPUs, SoC ASICs, and specialized modules, optimized for low power consumption and high performance in applications like video analytics, security, and robotics. By enabling real-time AI processing with support for multiple models on a single chip, DEEPX addresses the challenges of latency, privacy, and network costs associated with cloud-based systems. Its scalable architecture and 259 patents ensure cost-competitive, silicon-proven products for global markets.

Hailo develops AI processors optimized for deep learning applications on edge devices, enabling high-performance video processing and analytics with low power consumption. Their technology addresses the need for efficient AI inferencing in various industries, including automotive and industrial automation, by facilitating the deployment of complex neural networks in resource-constrained environments.

Qingwei Intelligent Technology designs and manufactures AI chips optimized for high-performance computing tasks in artificial intelligence applications. Their technology addresses the demand for efficient processing power in AI systems, enabling faster data analysis and improved machine learning capabilities.

Aivatech develops 3D-vision AIoT chips that integrate advanced facial and palm vein recognition technologies, RGB-D depth cameras, and vehicle license plate recognition systems. These solutions enhance security and automation in various applications, addressing the need for efficient and accurate identification in smart environments.

Singerno Microelectronics specializes in the design of digital-analog mixed-signal chips, enabling precise signal processing for various electronic applications. Their technology addresses the need for efficient power management and improved performance in consumer electronics and industrial systems.

Xinyaotu provides a full-stack integrated single-chip solution that combines intelligent sensors and computing with proprietary AI algorithms. This technology enables efficient data collection and processing for applications requiring real-time insights, enhancing operational performance in various industries.

Zhonghao Xinying develops specialized AI chips focused on enhancing computational efficiency for artificial intelligence applications. Their technology addresses the high energy consumption and processing limitations faced by current AI systems, enabling faster and more cost-effective AI deployment.

ThinkForce is a Shanghai-based manufacturer of artificial intelligence chips designed to enhance processing efficiency in machine learning applications. Their technology addresses the demand for high-performance computing solutions in industries reliant on real-time data analysis.

Key Foundry is a dedicated semiconductor foundry in South Korea that specializes in 8-inch wafer processing for analog, mixed-signal, power, and non-volatile memory (eNVM) applications. The company provides tailored online foundry services and multi-project wafer (MPW) programs to support the diverse manufacturing needs of its clients in the semiconductor industry.

Netrasemi designs and develops system-on-chips (SoCs) with a domain-specific architecture that enables real-time AI processing on edge devices, addressing the limitations of traditional chip architectures for embedded AI in IoT applications. Their SoCs provide high performance and power efficiency, facilitating the deployment of smart sensors and edge servers across various sectors, including surveillance and autonomous vehicles.

The startup develops a low-power system on a chip (SoC) with an integrated AI accelerator, designed for use in smartwatches, electronic shelf labels, and battery-powered IoT devices. This technology enables manufacturers to create energy-efficient smart devices that enhance user experience and functionality.

NEUCHIPS develops AI ASIC solutions, including the Evo Gen 5 PCIe Card and Gen AI N3000 Accelerator, specifically designed for deep learning inference in data centers. Their technology addresses the need for energy-efficient hardware that minimizes total cost of ownership (TCO) while enhancing performance for machine learning applications.

Timesintelli develops specialized System-on-Chip (SoC) solutions using its proprietary Domain-Specific Architecture (DSA) for edge AI processing, enabling efficient voice and visual data handling in various smart devices. Their AT series chips provide tailored support for multimodal human-machine interactions, addressing the need for cost-effective and energy-efficient processing in the AIoT landscape.

Rebellions develops AI accelerators that utilize HBM3e chiplet architecture and 5nm System-on-Chip technology to enhance energy efficiency and computational performance for deep learning applications. The company addresses the need for scalable and efficient AI inference solutions in the rapidly growing generative AI market.

Zenosic designs and develops high-performance network chips that enhance data transmission efficiency for AI, cloud computing, and IoT applications. The company addresses the need for robust networking solutions by leveraging its extensive R&D capabilities and a skilled team to deliver reliable chip products that support the demands of the intelligent computing era.

Exlords develops an AI and machine learning-integrated hardware platform for edge processors, enabling real-time AI inference on user devices through on-device neural processing units. This technology addresses the need for efficient, localized computing solutions that enhance performance and connectivity in heterogeneous computing environments.

Micro-nano core designs and produces IoT and AIoT system-on-a-chip (SoC) solutions focused on ultra-low power consumption. Their chips integrate sensor acquisition and embedded AI to improve the energy efficiency, precision, and edge inference capabilities of IoT devices.

Vastai Technologies develops high-performance AI chips specifically designed for computer vision and video processing, including the SV100 series for cloud-based inference and the VE series for edge computing. Their technology addresses the need for efficient, low-latency video analysis and processing in applications such as real-time video streaming and industrial automation.

Legendsemi designs and develops high-performance analog and mixed-signal chips for applications in telecommunications and consumer electronics. Their technology enhances signal integrity and reduces power consumption, addressing the demand for efficient and reliable electronic components.

NeuReality designs AI-centric infrastructure that integrates a network addressable processing unit (NAPU) with purpose-built software to streamline AI inference workflows. This solution reduces reliance on traditional CPUs and networking components, addressing the complexity and inefficiencies that hinder AI model deployment and scalability.

Eswin Computing designs integrated chips and solutions for display and video processing, AI data handling, and wireless connectivity. Their technology enhances multimedia system performance and improves data transmission efficiency in various applications.

Huixi Intelligent manufactures high-performance, low-power autonomous driving processors that utilize a unique "data closed-loop defined chip" methodology to enhance vehicle perception and decision-making. Their technology provides the necessary processing power for safe navigation in complex environments, enabling automotive companies to achieve cost-effective and scalable autonomous driving solutions.

Shanhai Semiconductor develops high-performance analog front-end (AFE) chips specifically designed for battery management systems (BMS) in energy storage and electric vehicle applications, providing precise high-voltage monitoring solutions. Their technology eliminates the need for calibration during production, streamlining the integration process for manufacturers and enhancing system reliability.

Seehi designs and manufactures artificial intelligence chips that enhance processing efficiency for machine learning applications. Their technology addresses the high energy consumption and performance limitations of traditional computing systems, enabling faster and more efficient AI computations.

Optical Standard Technology designs and manufactures silicon photonic computing chips and boards that utilize phase-change materials to enhance computational density and precision for AI applications. This technology significantly reduces deployment and operational costs in high-demand scenarios such as autonomous driving and large-scale data processing.

Myelin Foundry develops edge AI algorithms that process complex unstructured data from video, voice, and sensors in real-time, optimizing performance on low-power devices. This technology enables enterprises to achieve immediate insights and automation, reducing operational costs and enhancing user experiences.

Cortica provides an autonomous AI platform that converts visual, audio, radar and time‑series sensor streams into compressed neural signatures using self‑learning, brain‑inspired networks. The system trains on unlabelled production data, runs inference on low‑power hardware, and adapts continuously to avoid bias, allowing partners in manufacturing, automotive, security, and healthcare to deploy domain‑specific perception and analytics without building foundational models.

Jeejio develops AI-based chips specifically designed for Internet of Things (IoT) devices, enhancing their processing capabilities and energy efficiency. These chips address the limitations of traditional hardware by enabling real-time data processing and decision-making in resource-constrained environments.

Silicon Box specializes in advanced semiconductor integration, focusing on next-generation chiplet adoption solutions. The company operates a state-of-the-art foundry utilizing sub-5 micron technology for high-density packaging. They provide expertise across multiple sectors to enable scalable deployment of complex chiplet-based platforms.

Hanxu Technology develops specialized computing chips, including the SpinPU-M01 FPGA and SpinPU-M02 ASIC, utilizing spintronics to enhance performance in complex optimization problems. Their technology operates at room temperature and offers significant improvements in speed and accuracy over traditional computing methods, addressing the limitations of quantum computing.

HyperAccel engineers specialized AI semiconductors, utilizing a novel LPU architecture designed for high-performance and energy-efficient Generative AI workloads. Their product line spans from edge devices to cloud datacenters, offering optimized solutions for LLM inference. The company supports leading AI frameworks through a dedicated software platform, ensuring seamless integration for developers.

The startup develops smart cameras that utilize machine learning and IoT technologies to perform remote visual inspections of analog meters and other site elements. This solution enables clients to enhance operational efficiency and productivity by minimizing the need for on-site personnel during routine inspections.

The startup manufactures a chip that utilizes Compute Express Link technology to enable data center operators to efficiently pool and manage artificial intelligence accelerators, processors, and memory. This approach enhances system performance by providing adequate memory resources for diverse device integration, addressing the challenges of scalability and resource allocation in large-scale computing environments.

Aluksen Technology develops semiconductor chips utilizing LID optical identification technology to enhance data transmission rates in optical communication systems. Their solutions address the increasing demand for high-capacity, low-latency connectivity in 5G networks and data centers.

The startup develops digital power semiconductors that replace bulky analog components in traditional power systems with a single chipset and simplified circuitry. This technology reduces manufacturing costs and enhances performance consistency in power applications.

The company designs and manufactures high‑performance analog and mixed‑signal integrated circuits for power management, signal conditioning, and data conversion. Its products deliver efficient, reliable operation in demanding industrial and consumer electronic systems.

CVA Chip designs intelligent perception and computing control chips, including automotive-grade microcontrollers and image processing solutions, to enhance the reliability and functionality of electronic systems in vehicles and consumer devices. Their products meet stringent automotive safety standards and provide efficient performance for applications such as touch control and video processing, addressing the need for high-quality, safe electronic components in a rapidly evolving tech landscape.

proteanTecs provides a cloud-based platform that utilizes machine learning and on-chip monitoring technology to deliver real-time analytics on the health and performance of electronic components. This solution enables manufacturers to gain continuous visibility throughout the design, production, and operational phases, thereby enhancing reliability and reducing operational risks.

Lineyi Microelectronics designs and manufactures high-performance analog and radio frequency integrated circuits, specializing in magnetic isolation technology. Their products enhance signal integrity and reliability in electronic systems, addressing the need for robust performance in demanding applications.

Kuixin Technology provides integrated circuits that address computing power scaling and interconnection challenges. Their products cater to data centers, artificial intelligence, consumer electronics, automotive, and IoT applications.

EdgeCortix develops the SAKURA-II Edge AI Platform, an energy-efficient AI accelerator that delivers up to 240 TOPS for real-time inferencing in compact, low-power modules. This technology addresses the need for high-performance AI processing at the edge, significantly reducing operational costs across various sectors, including defense, robotics, and smart manufacturing.

Zhihe Computing develops high-performance, scalable AI computing CPUs based on the RISC-V architecture, enabling efficient processing for AI applications. The company addresses the need for advanced computational power in AI scenarios, leveraging a team with extensive industry experience to enhance performance and scalability.

NextSilicon's Maverick-2 Intelligent Compute Accelerator (ICA) utilizes software-defined hardware to dynamically optimize performance for high-performance computing (HPC) and artificial intelligence (AI) workloads. This technology eliminates the need for extensive code rewrites, significantly reducing development time and enabling faster insights across various applications.

Yiwei Semiconductor designs system-on-chip (SoC) solutions for robot motion control and synchronous positioning. Their technology provides precise and efficient control systems, essential for reliable automation in robotic applications.

Jingxin Microelectronics develops communication and information security chips, including RapidIO and PCIe bridge technologies, to enhance data transmission efficiency and security in embedded systems. The company addresses the need for domestically produced high-performance chips in China's infrastructure development, reducing reliance on foreign technology.

Weebit Nano provides Resistive Random-Access Memory (ReRAM) technology for semiconductor applications. Their embedded ReRAM IP and discrete chips offer faster speeds, lower power consumption, and higher endurance than traditional non-volatile memory, enabling advanced IoT, automotive, and AI devices.

Chiplego develops embedded high-performance computing systems that enhance mobile digital experiences by providing efficient processing capabilities. The technology addresses the need for robust computing solutions in mobile applications, enabling seamless performance in data-intensive environments.