EC.GAIA — AI Energy Optimization Engine | EC.DATA
EC.GAIA — AI Energy Optimization Engine
EC.GAIA is the AI layer of EC.DATA: predictive demand forecasting, automated setpoint optimization, and natural-language energy insights. Powered by Azure AI and trained on 10+ years of energy data.
AI Capabilities
- Predictive demand forecasting with 95%+ accuracy at 15-minute intervals
- Automated HVAC setpoint optimization based on weather, occupancy, and tariffs
- Natural-language energy Q&A — ask questions about your building's performance
- Anomaly classification: equipment fault, occupancy change, or weather event
- Energy conservation measure (ECM) impact simulation
- Automated monthly performance summaries with AI-generated insights
Technology
Powered by Azure AI Foundry (GPT-4o Vision), trained on 10+ years of multi-site energy data across 3 continents.
An AI copilot trained on energy data, not general chat
EC.GAIA is the AI layer that runs continuously against every telemetry stream from EC.EMS, setpoint from EC.BMS, and invoice inside your EC.DATA tenant. Unlike general-purpose chatbots, GAIA is purpose-built on operational energy data: its reasoning knows what a coincident peak is, how to adjust for degree-days, and when a drop in chiller COP is statistically significant.
GAIA surfaces recommendations automatically — "your AHU-3 minimum fresh-air setpoint is 15 percentage points above design, costing about $420/month" — and also answers natural-language questions like "show me every site where last month's demand charge was in the top decile for its building type".
Every GAIA recommendation is traceable to the underlying data and assumptions, so an energy manager can challenge the logic, adjust the parameters, and only then act. It augments rather than replaces the humans who own the savings.