Carbon
Energy times location-based grid intensity, with a carbon-price band rather than fake precision.
Footprint
Class1 computes carbon, water, and materials deltas on the same Monte Carlo draws as dollars, so the footprint has the same approval moment as the spend.
Why it sells
Carbon is not the same geography as water. A cheaper or lower-carbon region can still be water-stressed.
Class1 makes the tradeoff visible before architecture choices become production habits.
Second-currency method
A pull request can increase output length, fallback rate, context size, retry pressure, or tool schema load. Those same drivers affect energy. Class1 calculates footprint deltas on the same Monte Carlo discipline as dollars so the environmental exposure is tied to the software change, not to a generic annual sustainability estimate.
Carbon and water are separated because the best carbon answer is not always the best water answer. Region choice, grid intensity, WUE, and water scarcity can point in different directions. A governance report that collapses them into one green score hides the tradeoff the buyer needs to see.
Materials are treated honestly. API inference usually excludes provider Scope 3 because the customer cannot inspect the provider hardware inventory. Owned hardware, however, can include embodied carbon, material depletion pressure, and e-waste because the equipment choice is part of the customer's architecture.
Footprint buying triggers
Energy times location-based grid intensity, with a carbon-price band rather than fake precision.
Energy times WUE times AWARE scarcity. Water geography is not carbon geography.
Owned hardware includes embodied carbon, ADP materials pressure, and e-waste. API inference declares provider Scope 3 as excluded.
Provider carbon actuals can feed the same actuarial table pattern as cost actuals.