Portfolios run on systems nobody watches after six.
A building already generates most of what you need to run it well. The problem is that it lives in a BMS someone has to open, a spreadsheet someone has to trust, and a maintenance queue that meets neither. BeconixAI puts them on one screen.
What is already there.
From one reading to a closed job.
The same path runs on every vertical. What changes is what the signal is, what counts as wrong, and what closing it out actually takes.
Every asset, every meter, one screen.
Comfort you can measure
Unmet hours per space, actual against setpoint, valve and damper behaviour, and the data-quality gates that decide whether a verdict is even fair to draw.
Asset performance, analyzer by analyzer
Seventeen configurable analyzers score equipment on real behaviour — short cycling, saturation, drift against peers and its own baseline — with the ML signals shown, not hidden.
Energy with the anomaly on the chart
Consumption against the same period last week, month or year, calendar-aligned, with spikes, early starts, weekend running and cycling tagged on the series itself.
Alerts that become work
An alarm carries its suspects, its live values, its diagnosis and its history — and becomes a work order without anyone re-keying a thing.
From estate to endpoint, without changing system
Start at the portfolio: asset health, comfort scores, energy and open service cases across every site. Drill to the site that is dragging the average. Drill again to the floor, the unit, the point, and the fifteen-minute history behind the verdict. The trail is the product.
Evidence, not estimates.
How an improvement is proven depends on what it was. Energy work goes to IPMVP-style measurement and verification against a weather-normalised baseline. A reliability fix is proven by recurrence, or the absence of it, against the problem record. A pilot baselines your estate before anyone quotes a number.
Same core, different physics.
Every asset. Every meter. One platform.
A pilot baselines your sites before anyone quotes a number. Connect what is already there, instrument the gaps, and judge the platform on your data rather than a demo.