Baseline and opportunity study
We establish what you consume today, where it goes, and the three changes with the shortest payback.
Energy is one of the largest controllable costs a building or operation has, and one of the least watched. Intelligence makes it visible, then makes it smaller, and produces the ESG evidence as a by-product.
Sustainability work fails for a dull reason: the data arrives monthly, in a bill, aggregated, too late to act on. By the time anyone notices the anomaly, three months of it have already been paid for.
We meter at the level where decisions are made, model what consumption should be given weather and occupancy, and alert on the difference. The same data stream then produces the ESG and carbon reporting you are increasingly asked for.
Typical result: measurable energy savings and audit-ready ESG data.
If one of these is true we will say so in the first call, and tell you what to fix first.
We establish what you consume today, where it goes, and the three changes with the shortest payback.
Controls, scheduling and AI-driven setpoints implemented on a defined scope, with savings verified against the baseline.
Automated collection, calculation and audit-ready reporting, so the quarterly report stops being a manual exercise.
Every engagement starts with a free consultation and a written proposal. Scope, price and the measure of success are agreed before any work begins.
Sub-metering by floor, tenant, system or process, so a number has somebody's name attached to it.
Weather-normalised models of expected consumption, and an alert when reality drifts away from them.
Schedules, setpoints and control strategies tuned with AI, including recommendations your team can approve.
Scope 1 and 2 from your own meters, scope 3 where data allows, with the assumptions written down.
Audit-ready exports aligned to the frameworks you report against, produced from data rather than estimates.
Each recommendation costed, with payback period, so the decision is financial rather than ideological.
Twelve months of bills and whatever meter data exists, turned into a picture of where the energy actually goes.
Sub-meters and sensors where the picture is blurred, connected to the platform and verified.
Expected consumption learned from your own operation, not from a textbook building.
A ranked list of changes: the free ones first, then the cheap ones, then the capital ones with their payback.
Measurement after the change, so savings are proven rather than claimed, and reported the same way every month.
We agree the numbers before the work starts and report against them afterwards. These are the measures that usually matter for this service.
It depends entirely on the site, which is why we benchmark before promising anything. The benchmark itself usually pays for itself in the first few corrections it uncovers.
No. Any operation with a meaningful utility bill or a reporting obligation benefits, including single sites and small portfolios.
We specify and install what the site needs and remain vendor-neutral. You can buy the hardware directly if you prefer.
That is the design intent: measured data, documented factors, stated assumptions and a traceable method, rather than a spreadsheet of estimates.
Acta, non Verba.