Top 50 Edge Computing in Europe

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

VisionPlatform offers an AI computer vision platform that enables users to build and deploy custom models for tasks such as people and vehicle detection without any coding, utilizing edge computing for real-time processing. This solution addresses the complexity and time consumption associated with traditional computer vision development, allowing users to focus on data and achieve deployment in under ten minutes.

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.

Innatera provides ultra-low-power neuromorphic processors for edge AI applications. Their spiking neural processors enable real-time pattern recognition with sub-milliwatt power consumption and significantly reduced latency for battery-powered devices.

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.

Neurobus provides neuromorphic AI hardware and software that delivers sub‑millisecond inference at milliwatt power for edge‑deployed drones, ground stations, and space assets. Its radiation‑hardened processors and event‑driven sensor fusion enable autonomous perception, navigation, and swarm coordination without continuous human or ground‑station control. The platform includes a real‑time operating system, simulation tools, and open APIs for integration into aerospace, defense, and logistics systems.

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.

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.

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.

Synthara provides ComputeRAM™ in‑memory computing IP that integrates MAC operations directly into SRAM cells of standard ASIC/FPGA designs, eliminating external memory accesses. The drop‑in IP delivers up to 100× higher inference throughput and 100× lower energy consumption for edge AI workloads without increasing die area, enabling ultra‑low‑power devices such as wearables, drones and smart sensors. A cloud‑based validation suite models performance and power budgets to accelerate time‑to‑market for fabless semiconductor and OEM customers.

RaiderChip designs semiconductor hardware accelerators that enhance AI performance by addressing memory bandwidth limitations. Their solutions enable efficient AI inference for both edge and cloud applications, allowing users to run complex large language models locally with full privacy and without ongoing subscriptions.

promiseQ provides an AI-powered video security solution that reduces false alarms by over 90% and enhances real-time threat detection through advanced edge computing. The platform integrates seamlessly with existing systems, enabling efficient remote management and lowering overall security costs.

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.

Treon develops wireless edge products powered by the Treon Aito platform, enabling real-time data collection and processing for various IoT applications such as condition monitoring and asset tracking. The company addresses inefficiencies in physical operations caused by legacy systems and high asset intensity, helping businesses optimize maintenance, reduce costs, and enhance sustainability.

Byne provides a platform for building production-ready backends for LLM-powered applications, enabling users to create scalable LLM agents that can be deployed on-premise or at the edge. The solution addresses the need for efficient, high-performance AI deployment in environments with extreme scaling and privacy requirements, while also offering custom edge model optimization and data acquisition services.

Druid Software provides a software‑defined private cellular core, Raemis™, that runs on commodity hardware to deliver self‑contained 4G LTE and 5G SA/NSA networks. The platform aggregates multiple operator radio links, includes edge‑computing and network‑slicing capabilities, and supports massive IoT, enabling enterprises and vertical operators to deploy secure, low‑latency private connectivity on‑premise or in remote locations.

Vizgard provides edge-based visual autonomy software that automates the monitoring of time-critical systems using AI-powered insights and precision camera platform steering. This technology addresses the challenge of overwhelming sensor data by reducing operator fatigue and enhancing the efficiency of surveillance operations across various applications, including security and unmanned systems.

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.

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.

Floating Robotics provides a robotic manipulator equipped with cameras and edge computing to automate greenhouse tasks such as harvesting and de-leafing. This technology addresses labor shortages and rising operational costs by enhancing precision and scalability in agricultural practices.

VyperCore develops processor technology that accelerates compute-intensive applications by up to five times while completely eliminating memory vulnerabilities. This technology enables efficient resource utilization in managed languages, significantly reducing total cost of ownership for sectors such as fintech, edge computing, and healthcare.

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.

Frontier Robotics provides a platform-agnostic autonomy system for underwater inspections, integrating stereo camera technology with edge computing and SLAM for precise 3D mapping. This technology enhances the efficiency and safety of subsea operations, addressing the challenges of visual clarity and operational effectiveness in marine exploration.

MainStreaming provides broadcast-grade live video delivery using an EDGE network architecture that minimizes latency and optimizes bandwidth for large-scale streaming. The platform addresses issues of content piracy and network disruptions by employing AI-driven anti-piracy measures and real-time traffic management to ensure a high-quality viewing experience.

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.

Minima is a Layer 1 blockchain that enables edge devices to run full construction and validation nodes, creating a decentralized network without centralized control points. This technology enhances security and scalability while facilitating real-time peer-to-peer communication and energy-efficient token generation directly on devices.

Nomitri develops deep-learning Edge Embedded Visual AI solutions for retailers, enabling autonomous self-checkout systems that eliminate the need for costly camera installations and cloud infrastructure. Their smartphone-based technology enhances barcode scanning with intelligent loss prevention and product identification, significantly reducing operational costs and improving customer experience.

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.

The startup develops an AI platform for industrial machines that enables rapid training of complex visual inspection tasks by workers. This technology enhances the efficiency of quality control processes on production lines, allowing clients to implement AI-driven inspections at the edge.

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.

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%.

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.

Xelera Suite accelerates data center and cloud workloads by utilizing DPU and SmartNIC technologies to enhance network throughput and machine learning model performance. This software reduces compute latency and energy consumption, enabling efficient processing for applications in cybersecurity, telecom, and edge computing.

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.

Brill Power's Battery Intelligence Platform utilizes advanced battery and power management, edge computing, and data analytics to enhance the performance and lifespan of batteries in electric vehicles and stationary energy storage. The platform achieves up to 60% longer battery life, 46% improved performance, and 30% lower lifetime costs, while reducing emissions by 50%.

Danelec offers a cloud‑enabled platform that standardizes real‑time data capture from onboard sensors, providing unified analytics for fleet performance, fuel‑efficiency routing, and compliance with IMO, EU MRV, and CII regulations. The solution includes edge‑computing for offline reliability, open APIs, and modules for power monitoring, safety recording, and multi‑objective voyage optimization, helping ship owners and operators improve efficiency and meet regulatory requirements.

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.