What if every AI task had a better way?
Sustainability includes the planet, the people using intelligence, and the long-term economics of computing. This sandbox lets you compare available execution paths rather than assuming that local or cloud AI always wins.
1 · Define what matters
Quality is an illustrative external evaluation score, not a promise that an actual model would meet it.
2 · Compare possible paths
3 · See why
SAP's experimental core accepts declared requirements, evidence-labeled metrics, and available execution options. It returns an explainable choice, flags incomplete measurements, and never treats unknown energy use as zero.
Inspect the machine-readable plan
Inspect the draft execution receipt
Planned does not mean executed; executed does not mean verified. SAP Core does not independently measure AI workloads.
What this demonstrates—and what it doesn't
Planet: compare available environmental evidence, with explicit uncertainty.
People: preserve a local-only choice and the ability to see how a decision was made.
Economics: compare known operating costs without claiming universal savings.
This is a voluntary reference design. An AI platform must integrate the core into its actual model and tool execution path before these preferences can affect real behavior.