AI Cost & Quality Diagnostic

Find the waste without gambling on quality.

A five-working-day, provider-neutral analysis of one repeatable AI workflow. No production changes. No promised savings percentage. Just a defensible decision package.

What you receive

Evidence your technical owner can inspect.

Request-level trace

Tokens, estimated model cost, latency, retries, failures, and workflow stage.

Evaluation baseline

Representative cases, explicit rubric, and mandatory quality threshold.

Experiment matrix

Applicable tests across routing, caching, output controls, retries, batching, or local substitution.

Decision backlog

Accepted and rejected changes, limitations, expected impact, effort, risk, and rollback guidance.

Redacted scorecard

A clear before-and-after view that retains failed candidates instead of hiding them.

Findings walkthrough

A 45-minute review with the technical owner and a path to separately scoped implementation.

Five-day sequence

Day 1

Map + baseline

Confirm the workflow, cases, acceptance threshold, available usage data, and prohibited experiments.

Day 2

Trace + diagnose

Normalize tokens, cost, latency, retries, errors, repeated context, and frontier-model defaults.

Day 3

Controlled experiments

Test only relevant levers while preserving the original configuration and identical cases.

Day 4

Quality + economics

Reject regressions and calculate cost per successful run using disclosed rates and assumptions.

Day 5

Decision package

Deliver the scorecard, limitations, prioritized backlog, effort estimate, and rollback notes.

Good fit

  • The workflow already runs repeatedly.
  • You can supply representative sanitized examples.
  • Cost, latency, or reliability matters without sacrificing output quality.
  • A technical owner can approve the evaluation rubric.

Not the right engagement

  • You need an undefined AI strategy or a full application build.
  • The work requires emergency production repair.
  • Representative examples cannot be shared safely.
  • The outcome depends on guaranteed savings or an unreviewed production change.

Residual Forge / founding cohort

Know which AI costs are buying quality—and which are just waste.

Start a fit conversation →

Tell us which AI workflow you run repeatedly and where cost, latency, or quality is creating friction.