How we get there
Declare → Sweep → Rank → Prune → Report.
A recommendation isn't one model — it's a configuration: each step of your workflow gets its own model assignment. We test every combination of model-per-step, because the best model for one step is rarely the best for the next.
We publish the method. Parameterization stays ours.
The five stages
Every model, in every position, ranked on what it actually costs.
Stage 1
Declare
You declare the workflow: its steps, volumes, retry policy, budget gate, and the cost of a silent failure.
Stage 2
Sweep
Every model is tried in every position, and every combination across the workflow is evaluated — so each step ends up with its own model assignment. It is exhaustive by construction, not a hand-picked shortlist.
Ranking runs across every configuration. The forecast runs on the one we recommend.
Stage 3
Rank
Each configuration is ranked by true cost per delivered task — API spend plus modeled failure exposure: retries, abandonment, silent failures, and human review and rework.
Stage 4
Prune
The results are pruned using standard statistical methods — Monte Carlo ensemble, Pareto ranking, and sensitivity screens — the same disciplines already applied to balance-sheet and risk models in regulated finance.
Stage 5
Report
What ships is a ranked shortlist of the strongest configurations, with the benchmark figures behind each one, so the choice is yours to make on the criteria that matter to you. The answer tightens further once your own operating data replaces the benchmark assumptions.
Send us one workflow
We'll run it through all five stages.
What your workflow will cost, the most cost-effective configuration,
and where the money goes.
$15,000 introductory offer · one workflow.