Intelligence that compounds.
Every prediction compared to reality. Every season sharpens the models. Every baseline gets more precise. Month 12 saves more than month 1.
Measurable. Auditable. Compounding.
Set-and-forget is a myth.
The schedule that saved 20% in January saves 8% by June.
Weather patterns shift. Occupancy changes. Equipment degrades. Tariffs update.
Without continuous learning, optimization decays. Schedules go stale. Baselines drift. Savings erode.
Learn closes the loop.
Every action Optimize takes becomes training data. Every prediction gets scored against reality. Every gap between expected and actual becomes an opportunity to improve.
Three timescales. All running at once.
The system improves on three timescales simultaneously.
Single-site learning
Weekly timescale
Every day, baselines sharpen. The system learns that Tuesday loads look different from Thursday because of the weekly delivery schedule. It learns that the HVAC needs an extra 10 minutes of pre-cooling when outdoor temps exceed 35°C. It learns that Compressor 2 draws 12% more power when humidity is above 80%. After 30 days, the baseline is detailed enough to detect a 5% deviation. After 90 days, it detects 2%.
Seasonal adaptation
Monthly timescale
January's optimization strategy doesn't work in July. The system recognizes this. Pre-cooling windows shift as seasons change. Tariff strategies adjust as rate structures update. Equipment baselines recalibrate as ambient conditions change. After a full year, the system has a complete picture of how your building behaves across every condition — hot days, cold days, holidays, peak seasons, quiet periods.
Prediction vs reality
Continuous
Every optimization decision generates a prediction. “If I dim lighting by 15%, load will drop by 4.2 kW.” After the action, the actual result is measured: 3.8 kW. That 0.4 kW gap becomes training data. Next time, the prediction is more accurate. Over thousands of decisions, the gap shrinks from 10% to under 2%.
See learning in action. Three conversations. Three timescales.
These aren't hypothetical. These are the conversations that happen when a system is genuinely improving itself.
Accuracy Report
Monthly review · Tuesday
Energy Analyst
Online · Adelaide Gateway
Auditable accuracy. Actual numbers, tracked monthly, improving measurably. The finance team can rely on savings projections because they've been verified against reality.
Baseline Refinement
Thursday · Pattern detected
Energy Manager
Online · Adelaide Gateway
Nobody asked for this. Nobody spent a week analyzing load profiles. The system noticed the pattern, identified the cause, and refined its own baseline. Next Tuesday's optimization will be better because of it.
Six-Month Review
Monday · Quarterly review
Energy Analyst
Online · Adelaide Gateway
Compounding improvement, measured against its own history. The system genuinely gets better every month.
The Loop
Wattif works when you're not looking.
Four phases. Continuous cycle. Every 15 minutes.
Every 15 min
Sense
Every sensor, every meter, every signal — streaming in continuously.
Explain
Ask anything in plain English. Get a data-backed answer in seconds.
Optimize
Schedules adjusted. Loads shifted. Setpoints updated. Peaks shaved.
Learn
Baselines sharpened. Predictions compared. Models improved continuously.
Intelligence that compounds.
Every month makes the system smarter. Every season makes the savings deeper. See what continuous learning looks like for your building.
Talk to usOr email hello@wattif.io