One sentence conclusion: Using the usage details exported by your own backend, you can draw conclusions about where the costs are concentrated, how much is spent repeatedly, and how the usage changes - and you can recalculate each number yourself.
But this bill also has conclusions that it cannot give.We also write "cannot" in the report because it is as important as "can".
Phenomenon
When it comes to AI cost diagnosis, many people’s first reaction is: “Do I need to connect to your system first? Do I need to give you my account number?”
Not required.The input for cost diagnosis is only one thing: the usage details exported by yourself in the background.No need to connect to the system or account. This determines "whether the conclusion can be verified by yourself" - because the input is in your hands, the output can be recalculated in your hands.
Method: four steps, the order cannot be reversed
Step 1 · Fixed billing method.First, clearly state “what counts”: AI billing unit, number of times, or subscription. If you don’t do this step, all subsequent numbers will be just decoration.
Step 2 · Dismantle the structure.Depend on which model the money falls on, which time period, and which call form. What this step produces is "distribution", not "conclusion".
Step 3 · Locate the attributable portion.Find out thoseCan point to the specific location, and can be verified with the same bill after changespart. If you can't point it out, it's not attributable - it's better to let it go than to force it.
Step 4 · Give action.Each action must be able to correspond to the number of the previous step. What does not correspond is an opinion, not a conclusion.
What can this bill prove and what cannot it prove?
| Content | |
|---|---|
| Can prove | Total amount and trend; In which link the cost is concentrated (within the scope allowed by the field); What is the proportion of repeated overhead; Changes before and after the change |
| Cannot prove | Dimensions not included in the export. For example, when there is only summary and no details,Unable to calculate the proportion of specific links ——That is probably the biggest area of saving money. |
| What needs to be supplemented? | Clearly write "which fields are required for this section". After filling in the fields, it will be calculated in the next version. |
"It can't be calculated" will be written in the report instead of putting a number that looks like a conclusion on top. This is the difference between this report and "a good-looking PPT".
Conclusion
Just look at your own bills and you will get oneRecalculable diagnostics; What I can’t get is a sentenceCommitment。
How much you can save depends on your usage structure.Please refer to your revised bill. ——Any statement that "can save X%", you can ask it to give the algorithm.
Boundary (under what circumstances does this article not hold)
- The thicker the exported fields, the lower the lower limit of the conclusion: only the summarized bills cannot support the judgment of "which link is the most expensive". The correct approach at this time isComplete fields, it is not a change of conclusion.
- What this article describes is the method, not the results: there are no actual measured numbers or provinces in the article.
- If your usage structure has undergone major changes during the observation period (new functions, model changes), trend conclusions need to be re-viewed in segments.
How can you verify it yourself?
Use the same bill and double-count every number we gave you.If the recalculation fails, the conclusion is untenable.
This is also Tunenomics’ way of building trust with the outside world: it’s not “everyone else chooses me”, but “you can verify for yourself whether what I say is correct or not.”
Source and Description
- The report structure is based on the public instructions on the "Sample Report" page of this site.
- Source: Tunenomics Tunenomics unified external measurement basis (compare and review date: 2026-09-18).
- This article does not contain original customer data, actual measured figures and savings commitments.
This article is from Tunenomics’ “AI Cost Observation” series. The description of methods and the measurement basis of conclusions in the article can be checked; the numbers are marked with the source, measurement basis and date. Sample data does not represent actual results for any customer.