Sensing Layer
Real-Time Condition Sensing
- Device Data
- Environmental Data
- Load Conditions
L5 AI Optimization & Control Agent | Powered by PhyAI™
DeepChip Module AI Agent
Powered by DeepCtrls’ proprietary PhyAI™ lightweight algorithms, DeepChip integrates AI inference and control into a compact computing module. Designed for CDU, energy storage cabinets, MAU, and DHU applications, it enables on-device intelligence, second-level decisions, and closed-loop optimization.
Get Your Free Energy Savings AssessmentPhyAI™Lightweight AI
Plug & PlayStandardized Module
Real-Time ControlLocal AI Response
4 ApplicationsCDU / Storage / MAU / DHU
Product Overview
PhyAI™ Moves into the Device Control Layer
DeepChip embeds lightweight PhyAI™ into computing modules, enabling real-time sensing, local inference, and autonomous closed-loop optimization at the device level.
Compute-Control IntegrationAdaptive LearningInstant DecisionsPlug & Play
Inference Layer
PhyAI™ Edge Real-Time Optimization
- Model Inference
- Real-Time Optimization
- Safety Boundaries
Control Layer
Real-Time Closed Loop
- Command Execution
- Closed-Loop Execution
- Performance Validation
DeepChip Four Core Capabilities
Four Core Capabilities for Autonomous Optimization
DeepChip integrates sensing, inference, control, and validation into a standardized AI module, helping equipment manufacturers and users deploy Physical AI control with lower integration costs.
On-Device Intelligent Control
Powered by lightweight PhyAI™ algorithms, DeepChip delivers real-time inference and autonomous control at the device level, enabling fast response to dynamic loads and efficient operation.
Adaptive Continuous Optimization
Continuously adapts control strategies to changing loads and equipment conditions, maintaining optimal performance over time.
Standardized Plug-and-Play Integration
Built with standardized interfaces and protocols, DeepChip enables rapid integration into CDU, energy storage cabinets, MAU, and DHU systems with minimal system changes.
Measurable Results
Tracks power, energy, and control changes to validate optimization results with visible and traceable performance data.
Applications
Four Plug-and-Play Device Applications
DeepChip integrates PhyAI, edge computing, and closed-loop control into plug-and-play modules.
CDU Applications
Key ApplicationsAI Closed-Loop Control for CDU
CDU Applications
Key ApplicationsAI Closed-Loop Control for CDU
DeepChip enables local inference and rapid control to optimize flow, temperature, and cooling efficiency.
Liquid Cooling ControlLoad AdaptationEnergy Optimization
Battery Energy Storage Systems (BESS)
BESS Charge & Discharge Optimization
Battery Energy Storage Systems (BESS)
BESS Charge & Discharge Optimization
Optimizes charging strategies based on load, pricing, SOC, and battery conditions to improve efficiency and extend battery life.
Charge & Discharge OptimizationPeak-Valley OptimizationBattery Protection
MAU Applications
MAU AI Adaptive Control
MAU Applications
MAU AI Adaptive Control
Dynamically optimizes operation based on environmental conditions and fresh air demand, balancing process stability and energy efficiency.
Load AdaptationTemperature & Humidity ControlEnergy Efficiency Optimization
DHU Applications
DHU AI Adaptive Control
DHU Applications
DHU AI Adaptive Control
Optimizes dehumidification output based on humidity loads and operating conditions, improving precision while reducing unnecessary energy consumption.
Humidity Load AdaptationPrecision DehumidificationEnergy Reduction
From Module AI Agent to Active Liquid Cooling Control
DeepChip brings on-device AI intelligence into CDUs, enabling real-time inference, closed-loop control, and adaptive optimization across liquid cooling systems — from cooling loops to leak protection and coolant health management.
Liquid Cooling Landscape & Control Challenges
From Passive Response to Proactive Liquid Cooling Control
DeepChip brings PhyAI™ and industrial edge intelligence into high-density liquid cooling systems, enabling primary-side optimization, active thermal management, leak prediction, and coolant health monitoring through on-device inference and closed-loop control.
Key Benefits
Four Core Capabilities for Intelligent Liquid Cooling
Primary-Side Global Optimization
Predictive Thermal Management for CDU Systems
Predictive Protection for Leakage Risk Control
Predictive Coolant Health Monitoring
Customer Cases
Scenario Performance Validation
16%Liquid Cooling Energy Reduction
±0.5℃Typical Control Accuracy
≤5s Load Response Time
Validates liquid cooling system response speed, temperature stability, and energy efficiency optimization under dynamic load conditions.
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