A method for finding out what each AI workload costs per accepted output and which ones could use cheaper models, before anyone changes routing.
What the baseline diagnostic covers
The asset walks a diagnostic lead through the workload inventory, cost per accepted output, task success and latency, task sampling, failures, claim grading, and sign-off. It ends with a diagnostic questionnaire and an evidence inventory.
- Inventorying AI workloads and spend
- Measuring cost per accepted output
- Measuring task success and latency
- Sampling tasks across model tiers