Edge AI Companies

Intel

Santa Clara, United States

Intel designs and manufactures CPUs and AI accelerators, including its Gaudi line for deep-learning training and inference and AI capabilities integrated across its Core and Xeon processors.

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.

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.

SiMa.ai

San Jose, United States

SiMa.ai is a fabless chip company delivering a software-centric machine-learning system-on-chip (MLSoC) for low-power edge devices, targeting the 5-25W range for computer vision and multimodal generative AI. Founded by former Groq COO Krishna Rangasayee, it has raised $270M.

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.

Humane

San Francisco, United States

Humane is developing an AI-powered wearable device intended to replace smartphones, offering a hands-free, AI-first computing experience. Their core technology centers on a personalized, contextually aware AI assistant running primarily on-device via edge computing. The company aims to disrupt mobile computing by offering a screenless and more intuitive interface for everyday tasks and information access.

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 is a Japanese deep-learning company applying AI to manufacturing, robotics, healthcare, and materials. It co-develops the MN-Core line of AI accelerators and created the Chainer framework.

EdgeCortix

Tokyo, Japan

EdgeCortix is a Tokyo-based fabless semiconductor company designing energy-efficient AI processors for the edge with a software-first architecture. Its SAKURA accelerators deliver high AI throughput at sub-10-watt power and have received substantial NEDO R&D backing.

DEEPX

Seoul, South Korea

DEEPX is a South Korean fabless semiconductor company developing low-power AI chips for on-device inference in robotics, cameras, and consumer electronics.

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.

Digua Robotics

Beijing, China

Digua Robotics (D-Robotics), spun out of Hong Kong-listed Horizon Robotics in 2024, provides development infrastructure and computing chips for consumer and industrial robotics, supporting China's push into embodied AI. It raised a $100M Series A.

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

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.

Rabbit

Los Angeles, United States

Rabbit develops a consumer AI device, the r1, designed to execute tasks via voice and text prompts. Their core technology centers around a Large Action Model (LAM) – an alternative to traditional Large Language Models – that learns to automate actions across digital services without requiring dedicated app integrations. Rabbit targets everyday consumers seeking a hands-free, AI-powered interface for common digital tasks, and garnered significant pre-order demand for the r1 despite concerns regarding its reliance on user-configured OpenClaw.

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.

Helin

Rijswijk, Netherlands

Helin is a Dutch industrial edge-intelligence company whose Polaris platform runs real-time monitoring, analytics and AI at the edge to turn remote assets in oil and gas, renewable energy, maritime and manufacturing into connected, optimized operations. Its software brings predictive insight and control to equipment in low-connectivity environments.

GEMESYS

Bochum, Germany

GEMESYS, a spin-off from Ruhr-University Bochum, develops analog memristor-based AI chips that use ReRAM crossbar arrays for fully analog neural-network processing, enabling on-device training and inference for power-constrained edge hardware. It raised an 8.6M-euro pre-seed in 2024.

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

Cupertino, United States

Aizip builds the world's smallest, most efficient AI models for edge and endpoint devices, spanning vision, audio, time-series, language and sensor-fusion tasks such as keyword spotting, ECG analysis and on-device chatbots. Founded in 2020 in Cupertino by Yan Sun and Yubei Chen.

Axelera AI

Eindhoven, Netherlands

Axelera AI builds the Metis AI processing platform for edge inference (computer vision, robotics, industrial), delivering up to ~214 INT8 TOPS at high efficiency. Headquartered in Eindhoven, founded 2021; raised a $68M Series B in June 2024, bringing total funding to about $120M.

Blumind

Toronto, Canada

Blumind designs ultra-low-power analog AI chips for always-on edge applications (wearables, IoT, medical devices), claiming 100–1,000x energy savings versus conventional AI silicon, starting with its BM110 and BM210 processors. Founded in 2020 in Toronto by Niraj Mathur and John Gosson; raised a C$20M Series A in 2025.

DeepMentor

Taipei, Taiwan

DeepMentor (滿拓科技) provides miniaturized, low-bit AI IP and full hardware/software solutions—from CNN vision/audio models to large language models (7B–180B)—optimized for edge deployment, with automated AI-chip design tooling. Founded in 2018 in Taiwan by Jack Wu.

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.

Plumerai develops 'Tiny AI'—extremely efficient on-device vision models (using binarized neural networks) that run person, vehicle, animal and package detection plus face recognition on low-power cameras. Founded in 2017 (London and Amsterdam) by Roeland Nusselder and Taras Iakymchuk; raised over $17M.

Fastagger

Nairobi, Kenya

Fastagger is a Nairobi-based deep-tech company building edge AI infrastructure that lets machine-learning models run efficiently on low-power devices and affordable smartphones, even without internet connectivity. Founded in 2019, it focuses on bringing AI to low-connectivity environments across Africa and has partnered with Microsoft, Google and Safaricom.

roboGaze is a Hungarian automotive-software company building AI-driven driver monitoring that replaces expensive specialized hardware with computer-vision algorithms. Its Soteria system detects drowsiness, fatigue and distraction in real time and offers biometric driver authentication and fleet risk management. Founded in 2020 in Budapest, it raised a USD 1.7M round in 2022.

Qareeb

Algiers, Algeria

Qareeb is an Algerian company specializing in edge AI, IoT and on-device intelligence that runs locally without transferring data to remote servers. Its flagship Q-Farming system uses long-range LoRa connectivity to deliver smart-agriculture insights for irrigation and yield, while Q-Vision and Q-Access provide surveillance and biometric access control. It won first place for technological innovation at the 2025 African Union Youth Start-Up Awards.

TASS Vision

Tashkent, Uzbekistan

TASS Vision is an Uzbek computer-vision company that turns existing surveillance cameras into privacy-first retail analytics, processing video on-device at the edge. Its Vitrac and Sitrac products track customer journeys and shelf interactions for retailers, and its technology runs in over 2,000 stores across multiple countries. It has raised about EUR 1.5 million from investors including DOMiNO Ventures and 500 Global.

Hefring Marine

Reykjavik, Iceland

Hefring Marine is an Icelandic maritime-technology company whose Intelligent Marine Assistance System (IMAS) provides AI-driven, real-time decision support for vessel operators. It combines onboard sensor data, vessel-specific behavior models and analytics to guide safer, more fuel-efficient operation in changing sea conditions, building on the first patented wave-slam monitoring system. Founded in 2018 in Reykjavik.