Edge AI Companies

Intel

Santa Clara, United States

Intel develops AI accelerators including Gaudi, Xeon processors with AI acceleration, and neuromorphic chips. Major player in edge AI.

Horizon Robotics

Beijing, China

Horizon Robotics is a China-based AI hardware company specializing in edge AI processing units. They design and manufacture automotive-grade AI chips – the Journey series – specifically for advanced driver-assistance systems (ADAS) and autonomous driving capabilities. Targeting automotive OEMs and Tier 1 suppliers, Horizon Robotics provides a full-stack solution enabling on-device AI processing for improved safety and efficiency in vehicles.

Cambricon

Beijing, China

Cambricon is a Chinese fabless semiconductor company specializing in the design and development of Neural Processing Units (NPUs) for both cloud and edge computing applications. Their core product is a series of AI chips intended to accelerate machine learning workloads in servers, smart terminals, and robotics. Cambricon targets the growing demand for on-device AI processing and integrated end-to-cloud AI solutions within the Chinese market and beyond.

Blaize

El Dorado Hills, United States

Blaize develops edge AI computing platforms and silicon utilizing their Graph Streaming Processor (GSP) architecture. Their platforms, including Blaize Pathfinder and Xplorer, offer a code-free software suite to simplify and accelerate AI application deployment from data center to edge devices. Blaize targets industries seeking to implement scalable, energy-efficient AI solutions for applications like computer vision, overcoming the limitations of traditional hardware and software approaches.

Mythic

Austin, United States

Mythic is a US-based AI hardware company developing the Mythic AMP™ analog processor for edge AI applications. Their technology stores AI parameters directly within the processor, eliminating memory bottlenecks and delivering significantly improved power efficiency and performance compared to traditional digital architectures. Mythic targets industries like robotics, defense, and security, enabling advanced, real-time inference at the edge with reduced energy consumption.

Preferred Networks

Tokyo, Japan

Preferred Networks develops deep learning technology for industrial applications, robotics, and edge AI. Creator of Chainer.

Axelera AI

Eindhoven, Netherlands

Axelera AI delivers the world's most powerful and advanced solutions for AI at the Edge with the industry-defining Metis AI platform.

DEEPX

Seoul, South Korea

DEEPX develops core technology for high-performance AI semiconductors with over 300 patents pending across the US, China, and Korea.

Kneron

San Diego, United States

Kneron designs and manufactures neural processing units (NPUs) optimized for edge AI applications. Their SoCs enable on-device AI inference, reducing latency and enhancing data privacy compared to cloud-based solutions. Kneron targets smart home, automotive, and industrial IoT markets requiring low-power, high-performance AI capabilities directly within their devices.

Syntiant

Irvine, United States

Syntiant develops neural decision processors that enable on-device AI processing for ultra-low-power applications. Their core technology utilizes at-memory compute to deliver significantly improved efficiency and throughput compared to traditional microcontrollers when running deep learning models. Syntiant targets the mobile, earbud, and IoT markets, providing scalable hardware solutions for applications like voice control, always-on audio recognition, and vibration analysis directly on the edge device.

Particle

San Francisco, United States

Particle is a fully-integrated IoT platform providing hardware, connectivity, and cloud services for businesses deploying connected devices. Their core offering centers on edge computing capabilities, enabling data processing and device management directly on the hardware, reducing latency and bandwidth costs. Particle targets innovative companies building and scaling connected products across industries like industrial IoT, asset tracking, and connected vehicles.

Origin AI

San Francisco, United States

Here's a company description for Origin AI, based on the provided information: Origin AI develops WiFi-based motion sensing technology for indoor spatial understanding and home monitoring. Their core product utilizes radio frequency (RF) signals to detect and analyze movement within a home without requiring cameras or additional hardware. This technology targets the home security and smart home automation markets, offering privacy-focused activity detection and potential for advanced features like fall detection and occupancy-based energy savings.

LeapMind

Tokyo, Japan

LeapMind is a Japanese technology company specializing in highly efficient deep learning models optimized for resource-constrained edge devices. Their core product is a neural network compression technology that significantly reduces model size and computational demands without substantial accuracy loss. This enables the deployment of advanced AI capabilities – particularly in visual and audio processing – into applications like robotics, automotive systems, and IoT devices where cloud connectivity is limited or undesirable.

Wallaroo.AI

Seattle, United States

Wallaroo.AI delivers a platform for deploying and managing machine learning models directly on edge devices. Their core technology is a containerized, Kubernetes-native infrastructure optimized for low-latency inference and resource constraints typical of edge environments. This solution targets enterprises seeking to operationalize AI applications – such as computer vision and predictive maintenance – where cloud connectivity is limited or undesirable.

Twenty Billion Neurons

Berlin, Germany

Twenty Billion Neurons (TwentyBN) was a German AI company specializing in advanced video understanding and computer vision technologies. Their core product was a highly efficient AI platform for gesture recognition and object tracking, optimized for low-power edge devices. Acquired by Qualcomm, TwentyBN’s technology is now integrated into Qualcomm’s product offerings, targeting applications in mobile, automotive, and IoT devices requiring on-device AI processing.

AIStorm

San Jose, United States

AIStorm develops charge-domain computing chips and IP that deliver AI, memory, and digital processing directly in silicon—up to 100× more efficient.

Plumerai develops Larq, an open-source library for training and deploying extremely efficient binarized neural networks for edge devices.

Samsung AI

Seoul, South Korea

Samsung AI develops and integrates on-device artificial intelligence capabilities across Samsung’s consumer electronics portfolio, including smartphones, home appliances, and wearables. Key innovations center around their E2E Speech LLM solution – encompassing voice and sound AI – and advancements in vision AI for applications like real-time multilingual translation, audio enhancement (including noise reduction and source separation), and intelligent image analysis. This research aims to deliver enhanced user experiences through features like improved voice assistants, personalized content recommendations, and more intuitive device interactions, with a focus on efficient, on-device processing for privacy and responsiveness.

AIthena

San Francisco, United States

AIthena is the definitive Offline Edge GenAI Platform, empowering single-click deployment of private LLMs ensuring data sovereignty.

Aizip builds tiny AI models for edge and endpoint devices with 4 years of experience in consumer, hardware, and enterprise solutions.

Blumind

Toronto, Canada

Blumind makes AI accessible and sustainable with innovative analog AI chips for Edge AI applications in AIoT, robotics, and smart mobility.

DeepMentor

Taipei, Taiwan

DeepMentor provides miniaturized AI IP and complete solutions from CNN models to LLM models (7B~180B) for edge deployment.

Qualcomm AI

San Diego, United States

Qualcomm AI develops specialized semiconductor solutions that integrate AI processing directly onto mobile devices and edge computing infrastructure. Their core technology centers on AI engines embedded within Snapdragon platforms and dedicated edge AI compute, enabling on-device machine learning capabilities. This positions Qualcomm as a key enabler for applications requiring low-latency, power-efficient AI processing in areas like smartphones, automotive, and IoT devices.

BrainChip

Sydney, Australia

BrainChip develops and manufactures Akida, a neuromorphic computing processor IP designed for edge AI applications. This technology mimics the human brain to achieve ultra-low power consumption and efficient on-device processing of sensor data, eliminating reliance on cloud connectivity. BrainChip targets developers of edge AI solutions in markets like automotive, industrial automation, and smart devices where low latency and energy efficiency are critical.