Any organisation with land and buildings can list a hundred ways to cut its emissions. The hard part is knowing which few to do first.
That’s the problem I built Decarbonify to solve. It models an organisation’s whole estate — sites, buildings, rooms, equipment, land and vehicles — as a hierarchy of assets, estimates the emissions of each in a recognised standard (the Greenhouse Gas Protocol), and turns the result into a ranked, costed list of what to do first, with the saving and the assumptions shown for every recommendation.
I built it around a real portfolio — Bradwell Parish Council’s estate in Milton Keynes — and aligned it to the city’s Green Business Fund for local decarbonisation.
A few things I’m pleased with under the hood: an asset-type library that keeps growing, with AI helping classify assets and suggest inputs; transparent calculations where every number is a formula you can inspect, run in a safe arithmetic-only evaluator; and a design that stays fully usable whether or not the AI is switched on.
There’s a full write-up — what it does, why it’s useful, and the engineering behind it — plus a live demo you can click through yourself.
→ Read the case study and try it: decarbonify.mathewbest.com
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