Overview

The Economic Control Check answers one question: where does your Azure AI spend go, and how much of it can you account for?

It is an Azure Workbook and six KQL queries. They run inside your own Log Analytics workspace, against diagnostics your API Management gateway already emits. Nothing is transmitted to Metergrade, there is no account to create, and no credential is issued.

What it establishes

Question	Answered by
Can this workspace answer the question at all?	Preflight
What is being consumed, and when?	Observed consumption by day
Where does consumption concentrate?	Model and deployment distribution
How much has no accountable owner?	Attribution gaps
How much was spent on work that failed?	Failure and retry waste
What is worth testing before changing anything?	Validation candidates

What it does not do

It does not change anything. Every query is read-only, and read access to the workspace is sufficient throughout.

It does not identify retries. Proving that request B is a retry of request A needs client-side correlation that no gateway log carries. What the log supports is the waste retries produce — consumption under failed and throttled requests — and that is what is reported.

It does not recommend a change. The validation-candidates query ranks; it does not conclude. No threshold is applied, because the check does not know your quality, latency or reliability requirements. Turning a candidate into a verdict means testing it against those requirements, which is a deliberate step and not something a workbook tile should imply it has done.

It does not price anything. The queries report tokens, not currency. Applying your negotiated rates is a separate step, and a query that guessed at list prices would produce a number that looks authoritative and is not.

Where your data goes

Nowhere. The check has no upload step and makes no outbound call to Metergrade. The kit is plain text you can read before you run it, and the verification procedure lets you confirm the files are the ones Metergrade published without trusting anything we wrote.

Saving a baseline over time is a different mode with a different data boundary, and it is not built yet.