LLM Cost Optimisation with OpenAI GPT

We benchmark quality before and after every optimisation. A saving that quietly degrades output is not a saving, it is a deferred cost.

OpenAI GPT is strongest at the widest tooling ecosystem and mature structured-output support. For llm cost optimisation that matters because the failure modes of this kind of system tend to cluster exactly there.

The honest trade-off: cost at scale, and a data-handling posture that some regulated buyers will not accept without an enterprise agreement. We say that up front because a stack chosen for fashion rather than fit becomes someone's migration project two years later. We start from the constraint, not the capability, what the system must never do, who signs off, and what happens when it is wrong.

You own the code, the models where they are open-weight, and the documentation to run it without us.