Guides
Guides to AI workload economics
Practical notes for teams choosing between AI models and providers. Each one explains a method; figures shown are synthetic.
- Why the cheapest LLM per request can cost more per result
Cost per successful request, a worked synthetic example, and the conditions the number depends on.
- How to compare LLM providers for one workload: a checklist
Seven steps from a fixed success check to evidence someone else can reproduce.
- AI workload procurement: choosing models and providers on evidence
Buying AI capacity per workload: the success check, cost per successful result, hard constraints and the record behind the choice.
- How to check AI usage costs against provider list prices
Reported cost against a list-price estimate, missing and zero costs, and what a difference can and cannot tell you.
- Audit evidence for AI model and provider decisions: what to keep
Inputs, rules, fingerprints and a fixed reference time, so someone else can rerun the decision.
See it on a worked example
The AIYVO analyzer runs offline on a usage export you already have. On this site it is shown step by step on a synthetic export with fictitious models, so you can inspect every input, command and output.
Measuring one real workload? Read how an AIYVO pilot works or send a pilot-interest inquiry to jorge@aiyvo.com. It creates no account, subscription or commitment, and does not guarantee a pilot.