BIM Digital Twin Visualization
Built on BIM-based FMCS, it integrates source-grid-load-storage systems and visualizes multi-dimensional operational data in real time.
Compute-Energy Coordination & Energy Orchestration Platform
DeepOSAI-Native Energy Operating System
Powered by DeepCtrls’ proprietary PhyAI™ Engine, DeepOS connects computing, power, cooling, storage, and load systems to build a unified energy intelligence platform. It enables integrated energy orchestration, global optimization, and AI-powered predictive operations across AI data centers, smart factories, and intelligent campuses.
Get Your Free Energy Savings Assessment390+Leading Enterprise Customers
10%-40%System Efficiency Improvement
3000+Energy Station Data Sources
200+Physics-Based Models
Overview
What is DeepOS?
DeepOS is an AI-Native Energy Operating System that upgrades traditional energy platforms into an intelligent hub for modeling, simulation, optimization, and control.
Powered by PhyAI™ Electromechanical World Model, DeepOS unifies power, cooling, computing, storage, and loads into one intelligent system, enabling real-time sensing, predictive optimization, and closed-loop control.
Unified World Model
AI Predictive Maintenance
Compute-Energy Coordination
Source-Grid-Load-Storage
Physical LayerPV / ESS / Transformer / UPS / Chiller / CT / CDU / GPU
Model LayerPhyAI™ MEP World Model · 200+ Physics Models · Millions of Simulations
Application LayerCompute-Energy / Grid / Carbon / O&M / Digital Twin
Key Benefits
Four product values that keep the system efficient and safe
Powered by the PhyAI™ Engine, DeepOS enables closed-loop energy optimization through physical world modeling,real-time sensing, simulation, decision-making, and autonomous control.
MEP World Model
Unifies BIM, IoT, and real-time data to model power, cooling, storage, and computing systems for accurate simulation and autonomous control.
Capability Matrix
6 AI-Native Capabilities — From Energy Management to Energy OS
Powered by PhyAI™, DeepOS connects power, cooling, compute, storage, and loads into an end-to-end AI closed loop for sensing,simulation, decision-making, and control.
Compute–Power–Cooling Coordination
Integrates computing workloads, electricity prices, renewable energy, storage, and cooling demand to optimize computing, cooling, and energy resources through a coupled AI model.
Source-Grid-Load-Storage Coordination
Optimizes renewable energy, grid, load, and storage resources to enable peak shaving, demand management, and cost-efficient operations for zero-carbon factories and parks.
PDCA Cross-System Safety Coordination
With 280+ diagnostic rules and 1,900+ alarm models, DeepOS enables cross-system diagnostics and coordinated response, creating a centralized closed-loop safety management system.
FM Smart Operations & Maintenance
Reduces maintenance response time by 70%-80% with equipment records and smart work orders, enabling preventive maintenance, inspections, and collaborative facility operations.
ECMS Energy & Carbon Management
Analyzes energy consumption across types, time, space, and equipment, enabling carbon accounting, emission tracking, and decarbonization potential analysis.
Compute-Energy Coordination
Optimizing Compute, Power, and Cooling Coordination
Powered by the PhyAI™ compute-energy coupling model, DeepOS forecasts power, cooling, storage,and compute conditions, simulating millions of scenarios in real time to optimize AI data center costs and reliability.
Application Capabilities
Source-Grid-Load-Storage — Closed-Loop Control
DeepOS enables closed-loop optimization across power sources, grids, loads, and storage, integrating PV, thermal and electrical storage,and energy loads into a unified model for end-to-end optimization from design to control and operations.
For Energy-Intensive Net-Zero Factories & Campuses
10–20%Renewable Energy Utilization Improvement
20%+Peak-to-Valley Difference Reduction
10–20%Electricity Cost Reduction
≥90%Equipment Fault Prediction Accuracy
Applications
Key Applications of DeepOS
AIDC / AI Data Centers
AIDC / AI Data Centers
PUE optimization, compute-energy-cooling coordination, and renewable energy integration are key to improving efficiency and reducing operating costs.
Compute-Energy Coordination EngineReal-time coordination of power, cooling, and computing workloads.
Liquid Cooling Intelligent ControlRapid CDU response with stable coolant supply temperature control.
Source-Grid-Load-Storage OrchestrationImproved renewable energy utilization and reduced electricity costs.
Net-Zero Campus / Net-Zero Factory
Net-Zero Campus / Net-Zero Factory
For zero-carbon parks and factories, it dispatches PV, storage and load together, cutting total energy cost and carbon emissions while production continues undisturbed.
Source-grid-load-storage coordinationPeak shaving and demand control cut the total electricity bill
Renewable absorptionHigher PV self-consumption
Energy and carbon managementCarbon accounting and abatement potential
Healthcare / Transit / Commercial
Healthcare / Transit / Commercial
For hospitals, rail transit and commercial complexes, it keeps utility systems saving energy and running intelligently while comfort and operating safety are preserved.
System-level optimizationEnd-to-end optimization of heating, cooling and distribution
AI predictive maintenanceAbnormal-trend alerts reduce unplanned downtime
Intelligent work ordersInspection, repair requests and preventive maintenance in one
Customer Cases
Proven Results, Measurable Impact
National Supercomputing Center in Wuxi
AI-powered liquid cooling optimization improved HVAC energy efficiency by 24%+, saving 4 million kWh annually. PUE improved from 1.28 to 1.21.
More Customers
Reshaping Global Compute and EnergyInfrastructure with Physical AI
Proprietary PhyAI™ Physical AI Engine
10–40% Energy Savings, Verified in Real Time
390+ Customers Across Multiple Industries