How it works
Equipment-side sensing + predictive ML + contractor dispatch.
Step 1
A partnered contractor installs off-the-shelf sensors on your HVAC equipment: supply/return air temperature sensors, CT clamps for compressor and blower current, a humidity sensor, and (commercial tier) refrigerant-line temperature and pressure probes. A cellular or Wi-Fi gateway streams data to the cloud every 60 seconds.
Target install time: under 90 minutes for residential, 2–4 hours for commercial.
Phase 1 — Rule-based (launch)
Thresholds on current draw, temperature split, runtime, short-cycling. High precision, conservative.
Phase 2 — Anomaly detection (months 3–9)
Per-system baselines using z-score on residuals. Catches slow degradation that rules miss.
Phase 3 — Predictive ML (months 9–18)
Supervised models forecasting time-to-failure for specific failure modes.
Step 2
After ~30 days of data, the platform has learned your system's normal pattern — runtime cycles, temperature deltas, current draw at various outdoor temperatures. Each system gets its own baseline; we don't compare you to a generic average.
Rule-based alerts fire from day one. Anomaly detection kicks in once baselines are established. Predictive models arrive as labeled data accumulates.
Step 3
When an alert crosses a confidence threshold, you get a push notification with the predicted failure mode, estimated cost to ignore, and a one-tap option to schedule a visit from your contractor.
The contractor receives the diagnostic data with the dispatch ticket — not just "customer says it's warm." This means faster, cheaper visits and fewer "couldn't find anything wrong" calls.
Example alert
Compressor current anomaly
Your compressor is drawing 18% more current than baseline. Likely cause: low refrigerant or fouled coil.
Estimated cost to ignore: $42/month in extra energy. High risk of compressor failure within 60 days.
Step 4
Monitoring pays for itself in lower utility bills, not just avoided breakdowns. A system losing refrigerant or with a fouled coil can consume 20–40% more energy for months before failing. We quantify that.
Monthly reports show estimated kWh, comparison to your baseline, dollars saved, and CO2 avoided. Residential customers saving $25–40/month on energy are cash-flow positive from month one.