Jiangxingai provides an edge‑cloud AI platform for the energy sector that connects IoT sensors, cameras, drones and industrial equipment to deliver real‑time monitoring, automated inspections, and predictive analytics for substations, transmission lines, distribution rooms, charging stations and power plants. Its solution combines container‑based edge inference with cloud‑orchestrated model training and a virtual power‑plant management module, enabling utilities and large energy users to improve grid reliability, reduce manual patrols, and optimize carbon‑neutral operations.
Funding
Funding not disclosed
Founders
Product
Problem
Power grid operators and energy producers face challenges in monitoring vast, distributed assets such as substations, transmission lines, distribution rooms, and generation facilities. Limited visibility, manual inspections, and fragmented data hinder real-time fault detection, efficient maintenance, and integration of renewable resources, impacting reliability and carbon‑reduction goals.
Solution
Jiangxingai delivers an edge‑cloud AI platform that unifies IoT device connectivity, containerized services, and advanced analytics for the energy sector. The solution ingests data from sensors, cameras, drones and specialized equipment across smart substations, transmission corridors, distribution rooms, charging stations, and power plants. Edge nodes perform low‑latency inference using pre‑trained industry algorithms, while the cloud orchestrates model training, multi‑layer reasoning and centralized dashboards. Operators receive automated inspections, anomaly alerts, and predictive insights that support autonomous patrols, safety monitoring, and optimized dispatch of virtual power‑plant resources, thereby enhancing grid reliability and supporting carbon‑neutral objectives.
Target Audience
Primary customers are electric utilities, independent power producers, and large industrial energy consumers that require automated asset monitoring, virtual power‑plant coordination, and AI‑enhanced operational efficiency.
Features
- Edge‑cloud framework built on a lightweight, container‑based architecture with EdgeX Foundry integration for secure, scalable IoT device onboarding
- Over 100 industry‑specific AI algorithms for image, sound, vibration and protocol analysis, enabling automated inspection of substations, transmission lines, belts, turbines and renewable assets
- AI‑driven visual inspection via drones and fixed cameras with real‑time defect detection, safety hazard identification and automated reporting
- Virtual power‑plant management module that aggregates and controls millions of adjustable resources across industrial parks, base stations and buildings
- Integrated carbon‑intelligence tools for load balancing, green energy optimization and carbon‑peak/neutrality tracking
- Centralized web dashboard with multi‑level visualization, alert classification, and one‑click deployment of edge inference models
- Support for a wide range of industrial communication standards and real‑time control protocols, enabling plug‑and‑play deployment on existing equipment