A model of each building, built from twenty plain-language answers and its utility bills, and checked against every new bill. Where the energy goes, how the building compares, what it emits, what it costs per square metre and per suite, what to fix first, and every filing the address triggers — with each number showing where it came from.
No hardware · Bills and twenty answers are enough to start
Every step runs on the same record of the building. The model that answers "how are we doing" is the model that prices the fix and the model the audit is written from — not three that disagree.
"Mostly LED." "Newer double-pane." "Not sure." The address sets the climate station, the grid emissions factors and the programmes that apply. A photo of a nameplate counts as evidence and raises the accuracy tier.
Envelope, heating, cooling, hot water, lighting and plug loads are simulated daily and fitted to the bills on their exact dates — so baseload separates from weather-driven load, and a cold March separates from a wasteful one.
One computed sentence: how the building compares with the median for its type, what the gap costs a year, and whether use is up or down once the weather is taken out. The detail behind it is on the same page.
Every measure in the library checked against this building's own records: annual saving, cost, payback after incentives, NPV, SIR, carbon cut, and whether it moves the building off a stranding path.
Every programme the address triggers, with deadlines, readiness and penalty exposure in one place. When the work needs an engineer-signed audit, it builds on this record rather than starting a second one.
Screens below are the platform running on its demonstration portfolio, so the figures are sample data.
The address decides which programmes apply, and the platform holds 66 of them across the US, Canada and the global frameworks — including every active US building performance standard and the provincial and municipal Canadian requirements. Deadlines, readiness, penalty exposure and filing packs in one place.
The accuracy tier is computed from the data on file. Nobody at Quwa and nobody at the client can set it by hand. Every value shows its source, and when the bills and the building records disagree the page shows a finding rather than smoothing it over.
No. Bills and your answers are enough to start. Interval data and sub-meters improve the model later, and a monitoring deployment can feed it, but nothing has to be installed to get the first verdict.
No. The model starts from your answers and your bills. An audit is optional, and when one is needed it builds on the same record rather than starting a second one.
No. Portfolio Manager is the official benchmarking rail, and Q-Energy is built to sit on it — pulling data in and pushing filings out. What it adds is the model, the money and the compliance calendar that Portfolio Manager does not carry.
The platform proposes clearly labelled estimates for the exact billing periods that are missing, keeps them apart from the actual bills on every chart and table, and replaces them the day the real bills arrive.
Yes. Every table exports to CSV or XLSX, and every report pins the data and rule versions it was produced from, so a third party can reproduce a number rather than take it on trust.
Yours. Q-Energy holds whole-building and common-area data only, never resident-level consumption, and is run in line with PIPEDA. Access is per building and per role: owner, manager, board member, operator.
That is enough for a first verdict. Send us one building and we will model it and walk you through what came back — including the parts the model says it is not sure about.