Top 50 Edge Computing in Europe

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.

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.

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.

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.

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.

Avassa offers an application management platform designed for resource-constrained edge and IIoT environments, enabling secure and remote deployment, monitoring, and troubleshooting of applications across numerous edge locations. This solution addresses the challenges of managing distributed applications where connectivity is unreliable, significantly reducing operational overhead and enhancing efficiency.

CTHINGS.CO develops end-to-end 5G IoT solutions that utilize edge computing and non-intrusive data collection to extract actionable insights from industrial processes and assets. Their technology enables businesses to monitor energy consumption, machinery health, and environmental conditions, leading to improved operational efficiency and cost savings.

Little Place Labs utilizes machine learning and edge computing to deliver space-based insights within 7 minutes, significantly reducing data downlink requirements by up to 98%. This technology enables rapid disaster detection, threat monitoring, and efficient satellite health management, addressing the critical need for timely decision-making in various sectors.

The startup develops a modular orchestration software that integrates artificial intelligence and edge computing for drones and ground robots. This solution enables autonomous operations in applications such as surveillance, emergency response, and inspections, enhancing operational efficiency across diverse hardware and network environments.

AtlasEdge operates a distributed data center platform that provides colocation and connectivity solutions to enterprises, ensuring low latency and high performance for mission-critical IT infrastructure. The company addresses the growing demand for scalable digital infrastructure in Europe, enabling businesses to optimize their technology and network requirements efficiently.

Roofline provides a software solution that enables the deployment of AI models across diverse hardware platforms with a single Python call, optimizing and quantizing models for efficient edge computing. This approach addresses the challenges of traditional deployment methods, which often lack adaptability and performance, by significantly reducing memory usage and latency while maintaining accuracy.

Barbara is an Edge AI platform that enables industrial companies to deploy, manage, and monitor AI models and applications across distributed locations with minimal infrastructure complexity. It addresses the challenge of integrating and maintaining AI solutions on-site, ensuring efficient operations and real-time data processing without relying on cloud infrastructure.

Axelera AI manufactures AI acceleration hardware, specifically the Metis AI Processing Unit (AIPU), designed for efficient edge computing with up to 214 TOPS performance and 15 TOPS per watt. The technology addresses the need for cost-effective and energy-efficient solutions in generative AI and computer vision applications across various industries, including retail and security.

OctaiPipe provides a Federated Learning Operations (FL-Ops) framework that enables on-device AI deployment for Edge AIoT devices, minimizing data transfer to the cloud and enhancing privacy and security. This technology addresses the need for real-time decision-making and efficient management of critical infrastructure by ensuring localized intelligence and reducing vulnerability to cyber threats.

Kalray offers high-performance processing acceleration solutions powered by its MPPA® architecture. These solutions efficiently handle data-intensive workloads in AI, automotive, and telecommunications, delivering superior performance and energy efficiency for demanding applications.

Edgeless Systems develops confidential computing technology that ensures data remains encrypted during processing, protecting workloads from infrastructure-based threats. Their solutions enable organizations to migrate to the cloud while maintaining compliance with regulations like GDPR, CCPA, and HIPAA, without requiring code changes.

Gcore provides cloud and edge computing solutions that enhance content delivery, hosting, and security for businesses. By optimizing data transfer and storage, Gcore addresses latency and security challenges faced by companies operating in a digital landscape.

E-Space provides a sustainable low Earth orbit (LEO) satellite communication platform that connects billions of IoT devices globally, enabling real-time data transmission without reliance on commercial traffic. This system addresses the need for affordable, resilient connectivity in high debris environments, significantly reducing costs by over 90% compared to traditional LEO networks.

SynSense develops mixed-signal neuromorphic processors that achieve ultra-low power consumption and low-latency performance for edge computing applications. Their technology addresses the challenges of high energy use and slow response times in AI systems, enabling efficient real-time processing across various domains such as robotics, smart homes, and autonomous driving.

Teraki provides a suite of software development kits that utilize Edge-AI and machine learning to preprocess data from existing sensing devices, enhancing the quality of information for autonomous mobility applications. This technology enables the efficient integration of advanced functionalities in insurance, maintenance, and autonomous driving systems, improving safety and operational performance.

SEMRON develops a 3D-scalable AI inference chip using its proprietary CapRAM™ technology, which integrates compute-in-memory architecture to enhance energy efficiency and parameter density for AI applications. This technology addresses the high costs and power consumption of traditional AI chips, enabling efficient deployment of generative AI models directly on edge devices like smartphones and wearables.

The startup develops a deep-tech semiconductor chipset that enhances data movement by bringing data processing closer to computation. This technology improves the execution speed of large language models while increasing data privacy and energy efficiency.

Liquid AI develops non-transformer generative AI models, known as Liquid Foundation Models (LFMs), which require less memory while maintaining high performance across various applications. These models address the inefficiencies and high computational costs associated with traditional large language models, enabling scalable AI solutions for diverse industries.

Foundries.io provides FoundriesFactory, a cloud-native DevOps platform that accelerates the development and deployment of secure Linux and AI-based Edge products. It integrates CI/CD, testing, and secure OTA updates with the Linux microPlatform (LmP) OS, enabling OEMs to build and manage IoT devices efficiently.

SpiNNcloud Systems develops specialized hardware that replicates brain-like parallel processing to enhance real-time computing for complex simulations and data analysis. This technology overcomes the limitations of traditional computing architectures, significantly improving efficiency in handling large-scale data tasks.

Avesha provides a technology platform that enables efficient management and orchestration of application workloads across cloud, multi-cloud, and edge environments using predictive algorithms and automated scaling. The platform addresses high Kubernetes costs and inefficient GPU utilization by optimizing resource allocation and performance in real-time.

The startup provides a compute-intensive platform that enables organizations to optimize resource allocation for their workloads across on-premise, hybrid-cloud, and multi-cloud environments. By utilizing a sophisticated scheduler, the platform ensures efficient computing and resource utilization from any cloud provider and region simultaneously.

TechSeed offers end-to-end technology consulting to integrate IoT, Edge, and Cloud platforms for autonomous operations. They enable businesses to build digital twins and leverage AI and cybersecurity for enhanced efficiency and innovation across their technology stacks.

Literal Labs develops AI models based on Tsetlin Machine algorithms, which provide ultra-low power consumption and up to 250 times faster inference compared to traditional neural networks. Their technology enables on-device training and explainable AI, addressing the need for energy-efficient and transparent solutions in edge computing applications.

Kuafu provides an AI-powered platform that orchestrates distributed energy resources at the grid edge. It offers real-time visibility and predictive control to optimize grid operations, enabling stakeholders to unlock new revenue streams and support decarbonization efforts.

This company offers blockchain, 3D cloud, and decentralized hosting solutions to support businesses' digital transformation initiatives. They focus on serving industries like media, finance, science, and security with eco-responsible IT solutions.

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.

Provides a cloud-managed hypervisor that enables virtualization on x86 servers, supporting deployment in edge computing environments, small clusters, and private clouds. It simplifies server orchestration by centralizing management in a single console, reducing operational overhead, and automating updates, allowing users to deploy and scale virtual machines across multiple sites or customers with minimal manual intervention.

Neucom provides the ADA platform, a neuromorphic processing system that enables low-power, event-based computation for edge devices. Its Turing-complete architecture and user-friendly SDK allow developers to adapt complex algorithms, including post-quantum cryptography, for efficient implementation without prior spiking neural network expertise.

The startup offers a cloud-based Internet of Things platform that enables organizations to collect and analyze energy data for benchmarking building performance and predicting consumption costs. By providing alerts for abnormal conditions, the platform helps companies reduce energy consumption and optimize operational efficiency.

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.

Peeriot provides a low-code software suite that automates the collection, storage, processing, and sharing of IoT data, enabling self-organized devices and decentralized networks. This solution addresses the complexity and high costs associated with traditional IoT data architectures by simplifying data exchange and enhancing interoperability.

The startup offers a secured IoT-Blockchain platform that integrates various machine protocols without the need for coding, enabling businesses to manage their connected assets efficiently. This platform provides data sovereignty and user permission controls, allowing companies to leverage data-driven services at the edge while reducing time and costs associated with machine integration.

Scaleout offers a platform for secure data sharing and federated learning, enabling organizations to collaborate on machine learning projects while ensuring data privacy and compliance. This approach allows companies to enhance model training by leveraging combined datasets without compromising sensitive information.

Sensoworks provides a platform for real-time monitoring and control of complex infrastructure systems using edge computing and integrated data analytics. The solution enables predictive maintenance and anomaly detection, ensuring the security and efficiency of critical infrastructure operations.

BabylonAI provides a logging platform for computer vision teams that captures raw input and prediction data from edge devices, enabling efficient data organization by model version and device. This solution addresses the challenge of evaluating model performance in production environments, particularly in low-connectivity situations, while facilitating the collection of relevant data for retraining.

Weeteq is developing Ultra Edge®, a circuit-level AI and machine learning technology that enables real-time power and control system response correction at the device level. This technology enhances performance and energy efficiency for motor drive and power inverter manufacturers, while generating critical operational data for system-level platforms.

Copernilabs develops ThuliumX AI EDGE, a suite of artificial intelligence algorithms designed for real-time data analysis in devices such as cameras, drones, and robots, enhancing their detection and analysis capabilities. This technology addresses the need for faster threat detection and improved operational efficiency in various sectors, including security and infrastructure management.

MYWAI provides edge intelligence solutions for OEMs and machine tool vendors by integrating machine sensors and external esosensors to enable real-time data visualization and processing. Their platforms facilitate MLOps workflows and deploy AI algorithms on various infrastructures, enhancing equipment performance and enabling predictive maintenance and shipment tracking.

The startup manufactures an integrated power and communications device that combines uninterruptible power supply (UPS) functionality with internet connectivity. This device enables organizations to monitor real-time energy and data consumption, ensuring the continuous operation of critical systems and maintaining connectivity during power disruptions.

The startup offers a general-purpose computing platform that transforms microcontrollers into fully functional computers with memory protection and parallel execution capabilities. This technology enables developers to deploy secure, battery-operated IoT devices quickly and efficiently, ensuring stability and flexibility in their applications.

Enot offers neural network compression and acceleration tools to optimize AI model performance for faster inference and lower computational overhead. Their platform reduces model complexity and memory footprint, enabling efficient AI deployment on edge devices and in the cloud.

SmartEdge develops an In-Road Communications Network that utilizes solar-powered IoT devices to collect real-time traffic and environmental data while providing dynamic LED illumination for enhanced road safety. By leveraging AI-driven analytics, the platform delivers actionable insights that improve traffic management and reduce accidents by up to 70%.