# AI Service Cost Analysis Use Cost Management billing dimensions for Azure AI and Foundry spend. Do not claim token-level attribution unless a separate supported metric source returns token usage for the same resource and period. ## Attribution Order 1. Confirm scope, period, currency, service, and the requested attribution: service, account/resource, meter or product, deployment, project, model, or token usage. 2. Query `ServiceName` first, then narrow with separate bounded queries by `ResourceId`, `MeterCategory`, `MeterSubCategory`, and `Meter`. Reuse exact returned values as filters. 3. Treat `ServiceName` and `ResourceId` as direct billing attribution. Treat meter-to-model interpretation as indirect unless the returned meter unambiguously names the model and price shape. 4. Cost Management does not expose native deployment, project, request, input token, or output token dimensions. Do not invent them. Resource tags may help map a resource to an owner or project, but they do not prove that all cost belongs to that tag value. ## Correlate Usage 5. If a supported metrics source returns requests, tokens, throughput units, or deployment usage for the same resource and period, report it separately from billing cost. Derive unit cost only when the numerator and denominator have matching scope, time grain, and completeness. 6. Keep shared account charges, provisioned throughput, fine-tuning, storage, content safety, and other meters separate. Do not allocate shared charges to one deployment without a supported allocation source. 7. Preserve currency and period. If rows reach `top`, increase it to at most 5000 or narrow scope and label the result incomplete. ## Report Present the measured cost by service, resource, and meter; the requested attribution level; direct versus inferred mappings; any matching usage metrics; unallocated charges; confidence; and evidence gaps. For future spend or planned model pricing, hand off to `cost-estimation`. A dedicated Microsoft Foundry workflow should be added only when supported model, deployment, project, and account attribution is established.