As we deploy capital into green energy, we need to verify the "Greenness" of the AI models we support. We built a tool to estimate the carbon footprint of inference jobs based on grid location.
The Tech:
API integration with ONS (Brazilian Grid Operator) to get real-time generation mix (Wind vs. Hydro vs. Thermal).
Python script to map TWh to CO2e.
The Logic: if grid_mix == "100% Renewable": carbon_tax_credit = True
Why it matters: In 2026, "Green Compute" is a premium asset class. By quantifying it with code, we can value the companies providing it more accurately. We don't just trust the ESG report. We calculate the emissions ourselves.
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