ReasonRank

Keep engineering LLM costs competitive

ReasonRank exists so AI platform and product teams can prove which model (or harness) wins on a real workload — then bank the savings without guessing.

The loop

  1. Define the agent — one production workload + ≥5 shared test cases.
  2. Compare models — same suite, same scorers, your keys (BYOK) or your harness (BYO).
  3. Gate quality — non-inferiority / CI so “cheaper” never means “worse.”
  4. Project $ — volume from traces or an override → monthly savings.
  5. Verify — after you switch in prod, confirmed dollars show up under Savings.
  6. Stay awake — auto-eval + integrations catch drift.

Why the comparison holds up (vs. eyeballing dashboards)

  • Judges that earn trust. LLM judges are measured against your team’s own labels before their scores count, re-checked on a schedule, and flagged the moment they stop agreeing with humans. A judge never scores a run it’s also competing in.
  • Replay real episodes. Recorded production episodes become replayable fixtures — candidate models re-run against the tool results that actually happened, with no live side effects, so agent comparisons run on real traffic instead of synthetic guesses.
  • Dataset lineage. Every run pins an immutable, versioned snapshot of the eval set. “Which cases produced that number” is always answerable, and dataset diffs separate suite drift from model drift.
  • PR receipts. The CI gate posts the full diff — score deltas, confidence bounds, cost impact — as a PR comment, and can pin a frozen baseline run so “quality held” means held against the same bar.

Some of the above is in design-partner preview — ask and we’ll enable it for your workspace.

What “done” looks like for finance

A card you can defend: Agent X, same quality band, −$Y/mo on Z calls/mo, verified after deploy.

In-app guides

Signed-in docs hub: /guides (start with /guides/competitive-cost).

Also see: