Data Center Cooling - Use Cases

Data Center Operations

Data Center Cooling: Intelligent Chiller Management

Reduce energy consumption by 18% and eliminate unplanned thermal incidents with ML-driven monitoring and agentic corrective workflows.

Energy Savings

Less Downtime

Anomaly Accuracy

$0M

Saved

Challenge

Chillers account for 30-40% of total data center energy
Reactive operations miss early warning signs
Fixed maintenance schedules waste resources on healthy units
Thermal incidents cause costly emergency shutdowns

Solution

Four specialized ML models provide continuous health assessment while a 6-stage agentic workflow handles alerting, deep-dive analysis, field validation, and corrective actions with human oversight.

Predictive ML Agentic Workflow

1 Efficiency Model

2 Anomaly Model

3 Maintenance Model

4 Capacity Model

5 Continuous Monitoring

6 Smart Alert L1

7 Contextual Deep Dive

8 Field Validation L0

9 Corrective Actions

10 Oversight L2

Results

18%

Energy reduction

32%

Less downtime

45-min

Response time

$1.2M

Annual savings

Zero

Thermal incidents

Why Multi-Method Matters Here

ML Models MonitorFour specialized models track efficiency, anomalies, maintenance, and capacity

Rules Guard SafetyThermal thresholds and capacity limits are never overridden

Workflows CoordinateSix-stage process ensures proper validation at every step

LLMs ContextualizeDeep-dive analysis connects sensor data with operational history

Data Center Cooling: Intelligent Chiller Management

Challenge

Solution

Results

Why Multi-Method Matters Here

Deploy in 4 Weeks. See Results in 60 Days.