Core Infrastructure
ThermalSense — Thermal Intelligence Platform
ThermalSense
Data center operators face three thermal challenges that directly impact both costs and reliability: **Energy Waste from Overcooling**: Most facilities operate cooling systems conservatively to prevent hot spots, resulting in overcooling that wastes 20-40% of cooling energy. Without granular temperature data, operators can't safely reduce cooling capacity. The question "Can we raise the temperature setpoint?" has no confident answer. **Hot Spots and Thermal Stratification**: Airflow inefficiencies create localized hot spots where equipment runs above optimal temperature despite facility-wide cooling being adequate. These hot spots reduce hardware lifetime, increase failure rates, and limit rack power density. Traditional monitoring using a few sensors per room can't detect these pockets until they cause problems. **Reactive Management**: Cooling adjustments happen in response to alarms or complaints rather than predictive analysis. Workload changes alter thermal load, but cooling systems don't adapt. Seasonal weather variations impact cooling efficiency, but operations continue using the same setpoints year-round. The result is energy waste and increased thermal stress on hardware.
Who This Is For
**Data Center Facilities Managers** responsible for energy costs and equipment reliability, where cooling represents a major operating expense. **Infrastructure Directors** managing large-scale compute facilities who need to balance performance, reliability, and operational costs. **Sustainability Leaders** tasked with reducing energy consumption and carbon footprint while maintaining or expanding capacity. This is for data centers with 500+ kW IT load where cooling costs exceed $500K annually. If you're planning density increases, expanding existing facilities, or under pressure to reduce energy costs while maintaining uptime SLAs, thermal intelligence becomes essential.
What You Get
ThermalSense provides complete thermal observability and optimization for your data center. You gain real-time visibility into temperature distribution at rack-level granularity, predictive models showing how workload and environmental changes impact cooling needs, and automated optimization recommendations that reduce energy consumption while improving equipment reliability. Typical deployments achieve 25-35% cooling energy reduction and eliminate hot spots through optimized airflow management—often achieving ROI within 12-18 months from energy savings alone.
How We Work
Key Deliverables
1
High-Resolution Thermal Monitoring Infrastructure
Comprehensive sensor deployment providing complete facility visibility:
2
CFD (Computational Fluid Dynamics) Modeling
Physics-based simulation of your data center's thermal behavior:
3
Predictive Cooling Load Forecasting
Machine learning models predicting thermal demand:
4
Real-Time Hot Spot Detection & Alerting
Automated identification of thermal problems:
5
Automated Optimization Recommendations
AI-driven suggestions for energy reduction:
6
Integration with Building Management Systems
Seamless connection to your facility infrastructure:
7
PUE and Thermal Efficiency Dashboards
Clear visibility into facility performance:
8
What-If Scenario Modeling Tools
Planning capability for infrastructure changes:
9
ROI Tracking and Validation
Quantifying the value of thermal optimization:
10
Training and Documentation
Ensuring your team leverages the platform effectively: