It analyzes your energy use and infrastructure efficiency, measures the resulting emissions, and recommends concrete, prioritized actions to cut carbon — then tracks progress against your goals and compliance requirements over time.

It attributes energy use to workloads and converts it to gCO₂e across Scope 1, 2, and 3 — per service and per region — using cloud provider data and real-time grid carbon intensity, so the footprint reflects reality rather than annual averages.

It shifts flexible workloads — batch jobs, ML training, backups — to hours or regions where the grid is cleaner, using real-time and forecast carbon-intensity data. Typical reductions run about 10–30%, with wider flexibility windows yielding larger savings and no extra energy consumed.

Usually, yes. The biggest levers — rightsizing, eliminating idle resources, and moving to efficient processors — lower both emissions and spend, which is why carbon and cost are tracked side by side as first-class KPIs.

Reporting maps to the GHG Protocol and emerging disclosure rules such as the EU CSRD and California SB-253, with audit-ready evidence gathered automatically so disclosure isn’t a year-end scramble.

No. Latency-sensitive workloads are left untouched; only flexible, non-time-critical jobs are shifted, and efficiency actions like rightsizing are validated so performance and reliability are preserved.