Top 50 Edge Computing in Asia

The startup operates an IoT platform that utilizes deep learning inference on edge devices to gather and analyze real-world data. This technology enables businesses to efficiently deploy and manage edge computing systems, reducing operational costs and time to market.

The startup develops an AI-driven decentralized computing platform that integrates blockchain technology with edge computing protocols, enabling users to share computing resources and process data efficiently. By utilizing smart contracts and decentralized storage, the platform enhances transaction verification and provides reliable computing power for decentralized applications (dApps).

FeatherCloud provides 5G-based multi-access edge computing solutions that enhance data processing speed and reduce latency for applications at the network edge. This technology enables businesses to efficiently manage real-time data demands, improving performance for IoT devices and applications.

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.

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.

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.

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.

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.

Edge Matrix Computing operates a decentralized AI infrastructure that utilizes a GPU-based distributed computing network to provide scalable computing resources for AI applications. This platform addresses the inefficiencies of centralized computing by enabling developers to deploy and manage AI dApps with reduced latency and improved resource allocation.

Siliconwaves designs and manufactures multi-standard System-on-Chip (SoC) platforms, specifically the WAVE™ baseband chip, for communication and edge computing applications. Their technology enhances data processing capabilities at the network's edge, enabling low-latency and efficient data transmission for various sectors, including IoT and autonomous driving.

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-cost star tracker that employs edge computing and deep machine learning to process space data directly on satellites. This technology enables clients to analyze collected data in real-time, enhancing decision-making capabilities without the need for extensive ground-based processing.

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.

SkyServe provides a sensor-agnostic edge computing platform that enables the deployment of AI models on satellites to generate real-time geospatial insights. This technology addresses challenges in monitoring illegal activities, environmental changes, and resource management by delivering timely data for applications such as maritime surveillance and crop monitoring.

Mianbi Smart develops lightweight, high-performance AI models that efficiently run on mainstream consumer electronics and various terminal devices, optimizing computational resources for real-time applications. Their technology addresses the need for scalable AI solutions in edge computing, enabling advanced functionalities in mobile devices, wearables, and smart environments while significantly reducing inference costs and memory usage.

BGFRM develops AI-driven 3D visual inspection equipment utilizing distributed edge computing to enhance quality control in manufacturing processes. This technology enables real-time defect detection, reducing production errors and improving operational efficiency.

Super Rui Technology develops high-performance, energy-efficient multi-core processors based on the RISC-V architecture, addressing the need for reliable and secure computing solutions in various applications such as edge computing and autonomous driving. Their custom chip development services cater to specific computational requirements, enhancing performance and efficiency in demanding environments.

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.

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.

Taheng Wulian provides IoT solutions for the healthcare, industrial, and renewable energy sectors through real-time data analytics and sensor integration. The company enhances operational efficiency by optimizing resource management and monitoring, leading to reduced costs and improved performance.

IO River provides a unified layer of security, traffic control, and serverless computing across multiple Edge platforms, ensuring 99.999% availability and optimal performance for online services. By enabling dynamic traffic management and reducing infrastructure costs, the solution addresses the challenges of reliability and performance in multi-vendor architectures.

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.

CloudWalk Technology offers an AI platform that utilizes advanced facial recognition and edge computing technologies to enhance security and identity verification in the financial, public security, and aviation sectors. By providing real-time, accurate identification solutions, the platform addresses the critical need for improved security measures and streamlined access control in these industries.

Cloudwalk offers an AIoT platform that integrates edge devices, a collaborative operating system (CWOS), and multimodal foundation models to provide on‑device inference and standardized APIs for vision, speech, and language processing. The solution includes privacy‑computing, data‑governance, and AI‑Agent tools, allowing large enterprises and public agencies in finance, manufacturing, energy, and smart city domains to deploy AI capabilities without extensive custom integration.

The startup provides neutral hosting services by constructing 5G connectivity infrastructure, including edge computing and open radio access networks, across urban venues and buildings. This enables venue and building owners to establish reliable wireless connectivity, enhancing access to technology for their audiences.

Designs cost-effective, feature-rich System on Chips (SoCs) using the SHAKTI open-source processor framework, tailored for secure IoT devices and edge computing applications. These scalable, deep-embedded SoCs enable advanced functionalities like multi-camera connectivity, edge inference, and biometric processing in compact form factors, addressing the growing demand for reliable and secure semiconductor solutions in consumer electronics, automotive, and defense sectors.

SpacemiT develops high-performance RISC-V architecture computing chips that integrate cloud, edge, and device architectures to enhance data processing efficiency. This technology improves data access speed and reliability by mitigating latency and bandwidth limitations in distributed computing environments.

Sinh Micro develops a range of MCU and MPU chips tailored for edge devices in applications such as power management, device control, and human-machine interaction. Their technology addresses the need for high-reliability processing solutions in sectors like consumer electronics, industrial automation, and wearable devices.

Homebrew develops local AI solutions, including the Jan AI Assistant and the Ichigo real-time voice AI, utilizing energy-efficient hardware to enhance performance. The company addresses the need for accessible, efficient AI tools that operate without reliance on cloud infrastructure, ensuring user privacy and reducing latency.

Manufactures composite robots equipped with AI-driven technologies such as precise navigation, edge computing, cloud integration, deep learning, and multi-sensor fusion. These robots automate tasks in industries like biomedicine, electronics, and logistics, improving operational efficiency and reducing labor costs through standardized solutions for inspection, inventory, delivery, and disinfection.

Provides an AI-driven platform for optimizing deep learning models through techniques like model compression, pruning, and heterogeneous scaling. This enables businesses to reduce GPU computing costs by up to 80%, achieve up to 6x faster inference speeds, and deploy resource-efficient models on edge devices while ensuring data privacy and security.

CogniX develops a privacy-preserving AI-assisted yoga platform that utilizes advanced posture matching algorithms and edge computing to provide personalized feedback and guidance to practitioners. This technology addresses the challenge of limited access to qualified yoga instructors by enabling remote, customized instruction for thousands of users simultaneously.

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.

SandLogic develops Edge AI platforms and Computer Vision APIs that enable businesses to optimize their operational processes through deep learning and machine learning solutions. Their technology facilitates the integration of AI into existing systems, enhancing efficiency and accuracy in data processing across various industries.

Xsight Labs manufactures programmable Ethernet switches and software-defined accelerators for data centers and automotive applications, enhancing connectivity and resource allocation in high-bandwidth environments. Their technology addresses the challenges of network efficiency and scalability, enabling seamless integration with emerging 100G and 800G ecosystems while reducing power consumption.

Ivcloud provides a global interactive video cloud service that delivers ultra-high-definition, low-latency video streaming for applications such as cloud gaming and video conferencing. By shifting intensive visual computing tasks to powerful cloud servers, Ivcloud enables a wide range of devices to access immersive experiences without requiring high-end hardware.

Guoqi Intelligent Control develops a platform for intelligent networked vehicles that utilizes advanced vehicle-to-everything (V2X) communication technology. This platform enhances traffic management and safety by enabling real-time data exchange between vehicles and infrastructure, reducing congestion and accident risks.

This startup leverages edge analytics to deliver real-time AI surveillance solutions that enhance operational efficiency across various sectors. The technology provides immediate threat detection and response, significantly reducing the risks of security breaches and operational disruptions.

ByteTrade is developing a decentralized operating system, Terminus OS, that utilizes personal edge nodes and decentralized identifiers (DIDs) to enable users to maintain ownership of their data without reliance on centralized entities. This infrastructure addresses the lack of user control over personal data in the Web3 ecosystem by providing secure storage, private key access, and direct communication capabilities across multiple blockchains.

Hammerspace provides an automated data orchestration system that unifies and manages unstructured data across edge locations, data centers, and public cloud environments using a standards-based parallel file system architecture. This technology eliminates data silos, enabling organizations to optimize resource utilization and accelerate access to critical data for AI and high-performance computing applications.

Digital Edge is a data center platform that acquires and develops neutral data centers and digital infrastructure assets to enhance connectivity and scalability for businesses. By providing reliable and flexible data center solutions, it addresses the growing demand for efficient data management and storage in an increasingly digital economy.

Dtonic provides the Geo-Hiker™ spatio-temporal big data processing engine, which utilizes a distributed parallel architecture to enable efficient data aggregation, storage, indexing, and analysis. This technology reduces processing hardware costs by up to 90% and increases system speed by 40 times, addressing the challenges of high-volume data management in smart industries.

Fuya Intelligent develops an automated drone system that performs 24/7 surveillance and inspection tasks without human intervention, utilizing advanced flight algorithms and a cloud-based management platform. This technology enhances operational efficiency and data collection quality across various sectors, including security, energy, and environmental monitoring.

OPENEDGES Technology offers integrated memory subsystem IP solutions for ASIC and ASSP development. Their IP suite, including DDR PHY, memory controllers, and interconnects, optimizes power, silicon area, and DRAM performance for advanced computing applications.

Aethirs provides a decentralized cloud infrastructure that delivers on-demand access to enterprise-grade GPUs for AI model training and real-time gaming applications. This solution addresses the need for scalable, low-latency compute resources while ensuring high performance and security across a global network.

The startup develops an AI-based NeuroMosAIc Processor (NMP) that integrates a RISC-V architecture for high-performance computing in semiconductor applications. Its technology enables clients to efficiently evaluate neural network performance metrics such as accuracy, memory bandwidth, and run-time using SDK solutions compatible with TensorFlow, Caffe, PyTorch, and ONNX frameworks.

Macrometa provides a Global Data Network with Edge Compute capabilities, enabling businesses to build real-time applications and APIs while ensuring data protection. Their technology addresses performance issues by delivering sub-second page load times and improving SEO, resulting in increased conversions and reduced operational costs.

ZETIC offers a platform that automatically optimizes and deploys AI models for on-device execution across any hardware, framework, or device. Their service streamlines the workflow from model upload through benchmarking to integration with a three‑line code snippet, reducing deployment time from months to hours. By leveraging CPU, GPU, and NPU acceleration, ZETIC enables low‑latency, privacy‑preserving AI without requiring model retraining.

Vicharak develops the Vaaman edge computing board, which integrates a six-core ARM CPU with a reconfigurable FPGA to enhance parallel processing capabilities for applications like object classification and cryptographic algorithms. This technology addresses the limitations of traditional computing by providing a flexible hardware platform that accelerates performance in demanding edge AI and machine vision scenarios.

Monit delivers tailored IoT solutions that integrate sensor technology, edge computing, and cloud capabilities to optimize industrial operations. The platform provides real-time analytics and connectivity to enhance asset performance, improve decision-making, and drive efficiency across sectors like utilities, energy, and logistics. This technology enables scalable machine learning and intelligent automation for Industry 4.0 applications.