Top 50 Edge Computing

The startup operates a cloud computing edge platform that enables the deployment and management of virtual machines, server-less applications, and enterprise website security, including DDoS protection. This platform addresses the challenges of workload acceleration and infrastructure management, allowing developers and enterprises to enhance their operational efficiency and security.

The startup develops edge orchestration technology that utilizes device containerization to enhance safety, security, and intellectual property protection for resource-constrained edge devices. This technology enables developers to efficiently build, deploy, manage, and secure containerized applications on microcontroller and CPU-based systems with limited memory.

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.

Veea provides an integrated edge computing platform that combines hyperconnectivity, decentralized AI, and resilient security to enhance real-time data processing and reduce latency. The platform delivers last-mile internet connectivity to underserved communities, enabling critical services such as tele-education and smart agriculture while minimizing data transport costs.

Provides a cloud-native edge orchestration platform that extends Kubernetes-based deployment, management, and scaling to distributed edge infrastructure. It reduces cloud costs by up to 70%, decreases end-to-end latency by tenfold, and ensures secure, compliant operations through integrated SD-WAN and full-stack monitoring.

ZEDEDA provides a cloud-native orchestration platform that enhances the management, security, and visibility of distributed edge infrastructure using EVE-OS, an open-source operating system. The solution enables organizations to efficiently deploy and control edge applications in disconnected environments, reducing operational costs and deployment times significantly.

Azimuth AI develops application-specific integrated circuits (ASICs) tailored for edge computing applications, enhancing processing efficiency and reducing latency in data handling. The company's technology addresses the need for more sustainable and efficient computing solutions in resource-constrained environments.

Kneron develops application-specific integrated circuits (ASICs) and software that provide artificial intelligence tools for edge computing. Their technology enhances processing efficiency and reduces latency for AI applications in resource-constrained environments.

The startup utilizes a decentralized blockchain network combined with edge computing and AI to enhance data processing efficiency and security. It addresses the challenge of high latency and data privacy in distributed systems, enabling real-time analytics without compromising sensitive information.

Analog provides edge computing solutions that utilize smart sensors and mixed reality devices to enhance real-time data interaction in various environments. This technology enables organizations to better understand and engage with their surroundings, improving operational efficiency and decision-making.

The startup develops edge AI management software that provides technical and financial oversight for edge AI deployments. Its platform optimizes model supervision, data compression, and system learning, enabling companies to efficiently scale edge AI products while controlling costs.

Helin provides a managed edge computing platform that integrates real-time data collection from industrial assets with cloud-based analytics and remote AI applications. This solution addresses the challenge of siloed data infrastructures and high operational costs by enabling seamless deployment and management of edge applications with low latency and enhanced cybersecurity.

Fastagger develops software infrastructure that enables machine learning and AI models to run directly on edge devices, including lower-end smartphones, using techniques like multiparty computation and fully homomorphic encryption for secure local processing. This approach addresses the challenges of data privacy, constant internet connectivity, and the limitations of traditional cloud-based systems by allowing offline operation and cross-platform compatibility.

Lemony.ai by Uptime Industries is a ready-to-use B2B edge AI platform that enables businesses to deploy AI applications at the edge, minimizing latency and bandwidth usage. This platform addresses the challenge of integrating AI into existing infrastructure, allowing companies to enhance operational efficiency and decision-making in real-time.

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.

Xailient provides privacy-compliant edge AI solutions for computer vision applications, enabling secure face recognition, access control, and payment verification. Their technology allows businesses to deploy scalable automation across various sectors, reducing time to market and operational risks while enhancing customer experiences.

Provides a cloud-agnostic platform for orchestrating and automating edge-to-cloud ecosystems, enabling telcos and enterprises to manage infrastructure, connectivity, and applications from a single interface. Reduces latency, optimizes bandwidth, and lowers operational costs by supporting real-time workload automation and IoT device management at scale.

MemryX is developing an Edge AI Accelerator that employs specialized AI chip architecture to improve processing efficiency for edge devices. This technology enables real-time data analysis and decision-making in environments with limited computational resources.

NimbleEdge provides an on-device machine learning platform that enables real-time personalization for mobile applications, enhancing user experiences while maintaining data privacy. By processing user interactions locally, the platform reduces cloud infrastructure costs by over 50% and scales effortlessly to accommodate millions of daily active users.

HRDWYR develops AI-driven System-on-Chip (SoC) solutions that enhance data processing efficiency for real-time, edge-based decision-making in interconnected devices. Their technology addresses the limitations of current systems by minimizing energy consumption and environmental impact while delivering tailored, market-specific semiconductor products.

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.

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.

Ekkono Solutions provides an embedded software development kit (SDK) that enables edge machine learning for Internet of Things (IoT) devices, allowing them to learn from local usage patterns and perform real-time predictive maintenance. This technology enhances product functionality by enabling features such as auto-configuration and condition-based monitoring, ultimately extending product life and improving operational efficiency.

Armada provides an edge computing platform that integrates connectivity, ruggedized mobile data centers, and real-world AI applications to enable real-time data processing in remote environments. This technology addresses challenges in industries such as oil and gas, manufacturing, and logistics by enhancing safety, automating operations, and improving decision-making capabilities.

SecEdge provides a digital security platform that ensures device integrity and data privacy for IoT and Edge devices through silicon-level security and chip-to-cloud data encryption. The platform addresses the increasing threats of network breaches and regulatory mandates by offering a uniform security solution that is easy to deploy and manage across various semiconductor platforms.

EdgeRunner develops air-gapped Generative AI technology that operates locally on any chip, ensuring data privacy and security by eliminating reliance on cloud services. This approach allows enterprises to maintain ownership of their AI while achieving near-zero latency and reducing operational costs associated with data hosting.

The startup operates a renewable energy data processing platform that implements edge data services for smart cities, focusing on sustainable data usage and support for IoT applications. By integrating mobile data, telecom, and enterprise blockchain, the platform enables communities to enhance grid efficiency and reduce operational costs for both residents and businesses.

mimik provides a hybrid edge cloud platform that enables smart devices to function as both clients and cloud servers, facilitating real-time data processing and collaboration at the edge. This approach minimizes bandwidth usage and latency while enhancing security and data privacy, addressing the inefficiencies of traditional cloud computing models.

EDJX provides an edge computing platform that enables real-time data processing and application deployment closer to the data source. This reduces latency and bandwidth usage, enhancing performance for applications that require immediate data analysis and response.

Sunlight.Io provides a hyper-converged edge infrastructure platform that virtualizes high-performance workloads, enabling applications to run with bare-metal performance across numerous remote locations. This technology simplifies the management of distributed edge environments, reducing infrastructure costs by up to 85% and deployment times by 70%.

Klepsydra develops a software development toolkit and suite of libraries for edge computing, enabling real-time data processing on resource-constrained devices such as drones, robots, and autonomous vehicles. The platform enhances algorithm performance by processing up to ten times more data while reducing power consumption by up to 75%, addressing the challenges of data loss and delays in critical applications.

Pensando develops programmable processors and edge services tailored for enterprise and cloud computing environments. Their technology enhances data processing efficiency and reduces latency, addressing the challenges of managing increasing data loads at the network edge.

Stream Analyze offers a platform for developing and managing analytical AI models on autonomous edge devices, enabling real-time data processing with minimal operational footprint. This technology reduces data transmission by 10,000 times and accelerates decision-making, addressing the need for efficient analytics in industries reliant on connected devices.

The startup offers a platform for deploying and managing distributed computing and AI at the edge, featuring automatic scaling, application monitoring, and edge data processing. This technology enables clients to efficiently manage virtual machine migrations to containers and maintain SQL databases while analyzing electronic data interchange messages.

The startup provides an open layer for edge computing on the Solana blockchain, enabling developers to deploy decentralized applications with low latency and high scalability. This technology addresses the challenges of data processing speed and resource allocation in distributed environments, enhancing performance for real-time applications.

The startup offers a data collection and tracking solution for unconnected assets using low-power sensors and edge computing technology. This enables real-time visibility and management of assets that lack connectivity, improving operational efficiency and informed decision-making.

AnyLog provides a decentralized IoT platform that virtualizes edge data, allowing applications to interact with distributed data as if it were stored in a single database without transferring it to the cloud. This approach enables real-time insights and automated management of IoT data while ensuring data ownership and security for enterprises.

Provides an AI-powered edge computing platform that enables retail and hospitality businesses to optimize operations, improve customer experiences, and increase revenue. The platform offers device-agnostic infrastructure management, zero-touch onboarding, and a low/no-code application suite, including tools for inventory optimization and guest data analysis, ensuring 99.999% uptime and 50% cost reduction.

SmartHub.ai provides AI-ML powered edge automation and unified endpoint management for IoT devices, enabling real-time monitoring and management of operational technology assets. The platform enhances operational efficiency and compliance by predicting anomalies and automating maintenance across extensive edge infrastructures, significantly reducing downtime and operational costs.

The startup develops wire-free enterprise edge intelligence software that enables hospitals to accurately track the location and status of mobile equipment and personnel. By providing indoor positioning capabilities similar to GPS, the software enhances operational efficiency and asset management in healthcare environments.

Xcelerium develops high-performance domain-specific processors designed for edge computing applications, including wireless communications, radar, image signal processing, and computer vision. The company's technology enhances data processing efficiency and real-time decision-making in environments where low latency and high reliability are critical.

EDGEMATRIX develops Edge AI Boxes equipped with high-performance GPUs for real-time video analysis and processing at the edge, enabling efficient deployment of AI applications in smart city environments. Their technology enhances safety and operational efficiency by detecting anomalies and events through integrated camera systems, facilitating remote management and maintenance.

Edge is a mobile application that utilizes edge computing to process data locally on devices, reducing latency and bandwidth usage. It addresses the challenge of slow response times in mobile applications by enabling real-time data processing and analytics directly on users' devices.

The startup develops a distributed operating system based on a modified Linux kernel, specifically designed for embedded edge computing and the Internet of Things (IoT). This platform enables secure communications and efficient inter-networking, addressing the challenges of connectivity and data management in decentralized environments.

Axera develops high-performance AI System-on-Chips (SoCs) that utilize hybrid precision processing and pixel-level AI imaging technology to enhance edge computing applications in smart IoT, autonomous driving, and robotics. Their solutions address the need for efficient, high-quality data processing and imaging in complex environments, enabling advanced functionalities in various edge devices.

The startup provides an operating system specifically designed for edge computing environments, enabling efficient data processing and management at the network's edge. This technology addresses the challenges of latency and bandwidth limitations by facilitating real-time analytics and decision-making for IoT devices and applications.

Green Edge Computing develops a modular Edge Computing Appliance that integrates data processing, management, and networking for edge-optimized workloads in challenging environments. This compact solution reduces size, weight, and power requirements by over 75% compared to traditional IT equipment, addressing the need for efficient computing in space-constrained and resource-limited settings.

The startup provides location-based IoT services that utilize cloud-edge processing to enhance location estimation for navigation and tracking applications. By offloading power-intensive computations, the company enables businesses to implement robust authentication, security measures, and anti-spoofing techniques, improving the accuracy and reliability of their location data.

Izuma Networks provides a unified platform for deploying edge applications across various devices, enabling efficient management and scalability of distributed computing resources. This technology addresses the challenges of latency and bandwidth limitations in data processing at the network edge, enhancing real-time application performance.

This IT company provides cloud infrastructure-as-code for edge computing environments, enabling software deployment to distributed locations. They also offer interoperability solutions that standardize data across diverse platforms, along with reverse engineering and mission system design services.