01
Weather & heat
Forecast temperature, humidity, solar load, and extreme-heat conditions.
COOLING INTELLIGENCE OPERATING LAYER
CoolGrid Dubai Platform
One operational view to forecast demand, identify asset risk, prioritize energy actions, and strengthen cooling resilience before pressure becomes disruption.
COOLGRID / OPS-01
Illustrative platform environment
24–72h
Forecast horizon
6
Connected source types
4
Decision views
This is a product demonstration using synthetic data. It does not represent a live customer deployment or verified performance result.
INTERACTIVE PRODUCT DEMO
From fragmented signals to one prioritized operating picture.
Select a site, forecast horizon, and intelligence view. CoolGrid translates source data into forecasts, risk signals, and recommended operator actions.
Synthetic stream updated
Intelligence views
ILLUSTRATIVE DATA
This is a product demonstration using synthetic data. It does not represent a live customer deployment or verified performance result.
LOAD INTELLIGENCE
Cooling demand is building toward the afternoon peak.
Weather, occupancy, and historical load signals indicate a sustained rise from 14:00, with the highest system pressure expected near 17:30.
Downtown District Network
48 hours
Current load
68%
Predicted peak
87%
Peak window
16:30–18:30
Forecast confidence
91%
Forecast cooling load
87% peak
ForecastBaseline
Current+12h+24h+48h
Priority signal
Peak threshold approaching
Projected within 7 hours
Recommended action
Pre-cool priority zones
Review setpoint strategy before 14:30
Model confidence91%
CONNECTED DATA FOUNDATION
Use the systems operators already rely on.
CoolGrid is designed as an intelligence layer above existing operational systems. A pilot starts with available sources, establishes data quality, and expands only where additional signals improve decisions.
02
Building management
Setpoints, valve positions, temperatures, alarms, and equipment states.
03
Energy meters
Plant and asset-level electricity, demand, and energy-intensity profiles.
04
Equipment telemetry
Chiller, pump, AHU, vibration, pressure, and performance signals.
05
Maintenance records
Work orders, fault history, inspections, and asset service context.
06
Occupancy & schedules
Expected utilization, operating hours, events, and zone demand patterns.
Source systems
Secure ingestion
Quality & context
CoolGrid models
Forecasts · risks · actions
Pilot data principles
- Start with minimum viable data
- Keep operators in the decision loop
- Validate model output against site reality
- Define access, retention, and cybersecurity requirements before connection
PILOT PATHWAY
Prove operational value before deciding to scale.
A focused pilot is structured around a specific asset, operational question, and measurable validation plan—not a broad technology rollout.
01
Discover
Define the asset boundary, operational priorities, available data, and success measures.
Decision gate
Pilot brief + data inventory
02
Connect
Establish approved data access, map source systems, and assess quality and coverage.
Decision gate
Secure data pipeline + quality report
03
Calibrate
Configure baseline models and validate signals with engineering and operations teams.
Decision gate
Calibrated demo + validation protocol
04
Validate
Run forecasts and recommendations alongside operations without automatic control.
Decision gate
Pilot results + evidence review
05
Decide
Review value, limitations, integration needs, and the case for expansion.
Decision gate
Scale, refine, or stop decision
Typical pilot scope and timing are agreed with the operator after data discovery. No savings or performance outcome is assumed before validation.
Explore Grant PathwaySTART WITH ONE OPERATIONAL QUESTION
Bring us a site, a cooling challenge, and the data you already have.
We can assess whether a focused CoolGrid pilot is technically and operationally appropriate, then define a practical validation pathway with your team.