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Fogsphere provides an edge-first Physical AI Operating System that turns passive cameras, IoT sensors, and operational data into real-time intelligence for safety, security, and operational excellence. The platform combines computer vision, Visual Language Models, IoT telemetry, low-code automation, digital twins, dashboards, case management, and enterprise integrations to detect risks, understand context, trigger workflows, and generate auditable insights at the edge on sites, facilities, and distributed operations. It is designed for demanding industrial environments, prioritizing low latency, centralized governance, privacy, and extensibility. Fogsphere supports hundreds of safety, security, and operations use cases across industries and partners with NVIDIA Metropolis and Inception for large-scale deployments. Its goal is to help enterprises perceive, reason, and act in real time to move from reactive supervision to proactive, AI-powered operations.
Industries
Data & Analytics
Industrial & Manufacturing
Enterprise Software
AI & Machine Learning
Company Size
11-50
Company Stage
N/A
Total Funding
N/A
Headquarters
London, United Kingdom
Founded
2021
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Fogsphere advances physical AI at HANNOVER MESSE 2026 with MistIQ(R), NVIDIA Cosmos Reason 2 and ARM / Jetson Thor support. New capabilities across Fogsphere Manager and Vision Agent(R) expand enterprise training, reasoning and edge deployment for mission-critical industrial AI HANNOVER, Germany, April 20, 2026 - Fogsphere today announced at HANNOVER MESSE 2026 a broader expansion of its physical AI platform, combining the launch of Fogsphere MistIQ(R), new training workflows using NVIDIA Cosmos Reason 2, and expanded deployment support across ARM-based systems and NVIDIA Jetson Thor for edge deployment. Together, these capabilities give enterprises a more complete path to build, train, refine and operationalize real-world AI for industrial environments. Integrated into the Fogsphere Manager suite, MistIQ(R) is designed to help enterprises move from fragmented experimentation to production-grade physical AI. The platform provides a unified environment to train and refine Vision Language Models, World Models and AI Agents using operational video, sensor streams, event history, workflows and domain-specific knowledge from live environments. Fogsphere also announced contextual support within MistIQ(R) for NVIDIA DGX Spark(TM),powered by the NVIDIA GB10 Grace Blackwell Superchip, extending training and refinement options for compact, high-performance AI development at the edge. For manufacturing environments, Fogsphere is also introducing new training workflows for Vision Agent(R) using NVIDIA Cosmos Reason 2. These workflows are designed to help manufacturers build more context-aware visual agents that can interpret industrial scenes, reason over events across time and support plant-floor use cases such as unsafe behavior recognition, process deviation understanding, line-side hazard triage, quality inspection escalation and faster incident review. At deployment time, Fogsphere is extending operational flexibility with support for ARM-based edge architecturesincluding the high-performance NVIDIA Jetson Thor modules. This allows customers to operationalize advanced AI closer to production lines, work cells, material flow zones and other mission-critical points of operation where latency, privacy, resiliency and operational sovereignty matter most. By bringing training, reasoning and deployment into the same edge-first architecture, Fogsphere is creating a tighter continuous-improvement loop for physical AI. Customers can curate training inputs, evaluate reasoning quality, refine models and agents, and push updated intelligence back into the field through the same operational platform used to manage devices, sites, events, alerts and workflows. "Physical AI leadership will belong to platforms that connect training, reasoning and deployment in one operational stack," said Pasquale Giampa, CEO of Fogsphere. "With MistIQ(R), NVIDIA Cosmos Reason 2 workflows, and expanded ARM and Jetson Thor deployment support, we are giving enterprises a practical foundation to build adaptive AI systems that can be trained on operational reality and deployed where decisions matter most." The announcement reinforces Fogsphere's strategy of helping enterprises perceive, reason and act across physical environments. As industrial customers look for AI systems that go beyond isolated detections and static dashboards, Fogsphere is extending the platform to support more contextual, site-aware and continuously improving intelligence across manufacturing, energy, utilities, construction, logistics and other complex environments. About Fogsphere Fogsphere provides an edge-first AI platform for safety, security and operational intelligence. Through the Fogsphere platform, organizations can deploy real-time, multimodal intelligence that enables them to perceive, reason and act across physical environments. The platform includes Safety AI, Operational Intelligence AI, Vision Agent(R), no-code AI workflows and enterprise tools for deploying and improving AI across industrial and retail operations. Media Contact Fogsphere AI [email protected] +44 (20) 3879 4700
Fogsphere to deliver real-time perception, reasoning, and action at the edge with NVIDIA AI-RAN and Metropolis support. At NVIDIA GTC 2026, Fogsphere highlights how Vision Agent(R) combines live video, contextual reasoning, and edge-first AI infrastructure to help safety and operations teams move faster from detection to understanding to action. SAN JOSE, Calif., March 16, 2026 - Fogsphere today announced expanded support for Fogsphere Vision Agent(R) with NVIDIA AI-RAN and NVIDIA Metropolis, advancing how safety and operations teams perceive, reason, and act in real time at the edge. Built for edge-first deployment, Fogsphere Vision Agent uses Vision Language Models (VLMs) and agentic AI to transform live video into operational intelligence. The platform enables organizations to perceive what is happening across cameras and environments, reason over events across time and operational context, and act faster through real-time alerts, workflows, and response. With support for NVIDIA Cosmos Reason and Cosmos Reason 2 (CR2), Fogsphere is further strengthening its ability to deliver richer reasoning, clearer incident understanding, and faster action in complex industrial and construction environments. NVIDIA AI-RAN introduces a new class of distributed edge infrastructure by enabling AI and radio workloads to run on shared accelerated platforms. For Fogsphere, this creates a path to deploy perception and reasoning agents closer to where video is captured, helping customers identify hazards as they emerge, interpret unfolding situations in context, and trigger action immediately at the point of operation. This architecture supports scalable, real-time hazard detection, incident triage, and operational intelligence across large, distributed sites. Fogsphere's Vision Agent is designed to help customers move beyond alerts to real-time understanding and response. By combining VLMs, CR2, and NVIDIA Metropolis Video Search and Summarization (VSS), Fogsphere enables safety and operations teams to connect events across space and time, improve reporting consistency, reduce investigation effort, and shorten the time between detection and action. The result is a system that continuously perceives conditions in the field, reasons over operational context, and drives timely action to improve safety, security, and performance. "Fogsphere Vision Agent turns real-world video into real-time intelligence," said Pasquale Giampa, CEO of Fogsphere. "By combining advanced perception, contextual reasoning, and the ability to trigger action at the edge with NVIDIA AI-RAN, Cosmos Reason 2, and Metropolis, we are helping customers move faster from alerts to understanding and from understanding to action across complex environments." About Fogsphere Fogsphere provides an edge-first AI platform for safety, security, and operational intelligence. Through the Fogsphere Platform, organizations can deploy real-time, multi-modal intelligence at the edge that enables them to perceive, reason, and act across physical environments. The platform includes Safety AI, Operational Intelligence AI, Visual Agentic AI, and no-code AI workflows for industries such as energy, oil & gas, manufacturing, logistics, construction, mining, and retail. Media Contact Fogsphere AI [email protected] +44 (20) 3879 4700
NVIDIA, T-Mobile and partners integrate Physical AI applications on ai-ran-ready infrastructure. March 16, 2026 News Summary: * T-Mobile pilots NVIDIA RTX PRO 6000 Blackwell Server Edition AI infrastructure to demonstrate physical AI applications at the edge, complementing the AI-RAN Innovation Center's distributed network * Physical AI developers including Fogsphere, LinkerVision, Levatas, Vaidio and Siemens Energy are building reasoning and vision AI agents to the edge using the NVIDIA Metropolis Blueprint for video search and summarization (VSS) to integrate into T-Mobile's distributed edge network, with the City of San Jose among first to assess the technology. * The new NVIDIA VSS blueprint version 3 accelerates the development of reasoning video analytics AI agents through a flexible modular architecture, advanced multimodal visual understanding and integrated agentic search capabilities. GTC - NVIDIA and T-Mobile today announced they are working with Nokia and a growing ecosystem of developers to bring physical AI applications over distributed edge AI networks. This collaboration demonstrates how next generation AI-RAN infrastructure can transform the wireless network into a platform for distributed high-performance edge AI computing, creating a foundation for developers to deploy vision AI agents that understand the physical world across cities, utilities and industrial worksites using the NVIDIA Metropolis platform. NVIDIA's AI-RAN portfolio encompasses NVIDIA ARC-Pro built on NVIDIA RTX PRO(TM) 4500 Blackwell Server Edition for power-constrained cell sites, and NVIDIA RTX PRO 6000 Blackwell Server Edition for higher-capacity mobile switching offices. T-Mobile was the first in the U.S. to pilot NVIDIA's AI-RAN infrastructure with Nokia's anyRANsoftware and is now working with select NVIDIA physical AI partners, demonstrating how cell sites and mobile switching offices can support distributed edge AI workloads while continuing to deliver advanced 5G connectivity. "Telecommunication networks are evolving into the AI infrastructure enabling billions of devices - from vision AI agents to robots and autonomous vehicles - to see, hear and act in real time," said Jensen Huang, founder and CEO of NVIDIA. "By turning the 5G network into a distributed AI computer with T-Mobile and Nokia, we're creating a scalable blueprint for the world's edge AI infrastructure." "Turning networks into distributed AI computing platforms to unlock the full potential of physical AI will require ultra-low latency and space time coherency at the network edge for billions of endpoints, and that's what we've built at T-Mobile," said Srini Gopalan, chief executive officer of T-Mobile. "With the first nationwide 5G Standalone and 5G Advanced network, we are uniquely positioned to help power a future where intelligent systems don't wait on the cloud but rely on intelligent networks that allow them to act in real time." The Mobile Network as the Nervous System for Physical AI The transition to AI-RAN built on NVIDIA accelerated computing addresses a critical bottleneck in scaling physical AI: lack of low-latency, secure and ubiquitous connectivity. While Wi-Fi is limited by reach and security, T-Mobile's 5G standalone network provides the wide-area coverage and guaranteed quality of service required for complex AI agents to operate in busy city intersections, industrial facilities and rural areas. This architecture enables physical AI to offload heavy computation from the device to the nearest edge location. Shifting heavy processing to the network edge allows developers to streamline hardware requirements for individual cameras and robots, making it possible to cost-effectively scale sophisticated AI models across billions of interconnected devices. Leading Developers Bring Reasoning and Vision AI to the Edge A growing ecosystem of developers is collaborating with NVIDIA and T-Mobile to integrate physical AI agents that are driving real-time action, built with the NVIDIA Metropolis Blueprint for video search and summarization (VSS) on T-Mobile's distributed edge network. Pilot use cases include: * Smart City Operations: LinkerVision, Inchor and Voxelmaps are testing integrated computer vision-based "City Operations Agents" and a digital twin that can perceive, simulate and optimize traffic light timing, targeting 5x faster incident response times for the City of San Jose. * Automated Utility Inspection: Levatas and Skydio are automating the inspection of hundreds of thousands of miles of transmission lines over 5G with NVIDIA compute to detect and resolve anomalies such as leaning powerpoles, corrosion and thermal hotspots 5x faster. They are now evaluating AI-RAN infrastructure to further reduce costs, improve storm recovery time and accelerate the shift from reactive to predictive maintenance. * Vision-Based Facility Management: Developers such as Vaidio are using the VSS blueprint to build facility management agents that move beyond simple sensors to perform threat detection and failure forecasting, triggering automated workflows to improve facility management. * Real-Time Industrial Safety: Fogsphere provides safety AI agents for SAIPEM to detect and respond in real-time to hazardous events - such as workers under suspended loads or hydrocarbon spills - in high-risk construction onshore, offshore and drilling environments. Fogsphere is now validating how AI-RAN infrastructure can enhance the capabilities and performance of these agents - already running 24/7 without reliance on Wi-Fi - over secure and distributed network compute. These initiatives reflect T-Mobile's broader strategy to test and enable edge AI capabilities in collaboration with NVIDIA, Nokia and a diverse ecosystem of software providers, manufacturers and enterprise innovators. Accelerating Vision AI Agents Development With the Metropolis VSS 3 Blueprint While more than 1.5 billion cameras capture footage globally, less than 1% is ever reviewed by humans. NVIDIA is introducing the Metropolis VSS 3 Blueprint to enable agents to reason over video from the edge to the cloud. Key features of the blueprint's latest iteration include: * Agentic Information Retrieval: AI agents can decompose complex natural language queries and search across video footage to find specific events in under five seconds. * Modular Architecture: A flexible framework allows teams to adapt VSS 3 to diverse environments - from retail stores to warehouses - without overhauling core infrastructure. * 100x Efficiency: VSS can summarize long-form video up to 100x faster than manual reviews, drastically reducing repetitive tasks and review costs for global physical operations. Partners using the VSS blueprint to optimize operations and enhance safety across industries include Caterpillar, KION, Hitachi, HCLTech, Siemens Energy, Tulip and Telit Cinterion.
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Industries
Data & Analytics
Industrial & Manufacturing
Enterprise Software
AI & Machine Learning
Company Size
11-50
Company Stage
N/A
Total Funding
N/A
Headquarters
London, United Kingdom
Founded
2021
Find jobs on Simplify and start your career today