# Trade Mark Journal No.2025/029 18 July 2025

## UK00004217703 11 June 2025 (9,42)

nudgwatt

Class 9
  Computer software, firmware, and mobile applications for monitoring, management, control, analysis, and optimisation of energy usage, building operations, environmental performance, and utility systems; downloadable and recorded software for use in building automation, smart grid integration, predictive load balancing, and fault detection; software featuring artificial intelligence algorithms for decision-making, forecasting, anomaly detection, and optimisation of energy consumption; intelligent software agents and virtual assistants for real-time interaction with building and energy management systems; software modules for training and deploying AI models related to building and energy performance; Internet of Things (IoT) devices, edge computing hardware, programmable logic controllers (PLCs), gateways, transceivers, and embedded systems for acquiring, transmitting, and processing energy and environmental data; communication hardware for cloud-based virtual environments; user interface terminals, dashboards, and mobile apps for interacting with intelligent energy systems; APIs and SDKs for third-party integration and deployment of intelligent energy assistants in virtualised or hybrid energy management environments.
Class 42
  Provision of cloud computing services including Software as a Service (SaaS), Platform as a Service (PaaS), and Infrastructure as a Service (IaaS) for managing, analysing, simulating, and optimising energy use, building performance, and sustainability metrics; development, deployment, and hosting of intelligent cloud-based platforms incorporating artificial intelligence (AI), machine learning, and intelligent agents for predictive control, system automation, and optimisation; provision of AI-driven assistants and virtual agents for user interaction, system configuration, and automated decision-making within energy management environments; deployment of digital twins and simulation tools to model physical building and energy infrastructure within virtual environments; remote diagnostics, adaptive system tuning, and predictive maintenance supported by AI algorithms; cloud orchestration of virtual machines, edge devices, and control modules; creation and training of custom AI models and intelligent control agents for integration into smart buildings and infrastructure systems; technical consultancy and support for hybrid cloud platforms combining real-time and cloud-hosted intelligence for energy optimisation, carbon tracking, and smart environment control.

Thomas Joseph Edwards