Use case

Cost Reduction

A systematic hunt for the cheapest AI setup that still passes all your quality checks — so the bill goes down without the answers getting worse.

The short version

It's like shopping for a phone plan: you don't want the cheapest plan, you want the cheapest plan that still covers everything you actually use. We do the same with AI workflows — try cheaper configurations, keep only the ones that still pass every quality test, and pick the least expensive survivor.

How it flows
List the cost dialsTry cheaper setupsQuality gates filter themCheapest survivor winsSavings verified on billRepeat as models improve

The problem, in plain words

The monthly AI bill lands, bigger than last month again. You know cheaper models exist — new ones arrive constantly — but the last time someone downgraded a model to save money, quality dipped and nobody noticed for three weeks. So now nobody dares touch anything. The safe move is the expensive move, and the bill keeps growing while cheaper options pile up untested.

What we set up

The eval harness (the test bench that scores workflow versions against saved test cases) runs a guided search across everything that drives cost: smaller models, shorter prompts (the agent's instructions), narrower retrieval (fetching fewer documents per question), tighter tool budgets (fewer tool calls per task). Every candidate configuration has to pass the quality, latency (speed), and tool-reliability gates — fail any one of them and it's out, no matter how cheap. Among the survivors, the cheapest wins. Per-route cost tracking then verifies that the savings actually showed up on the bill, and the whole sweep is re-run quarterly, because the model landscape keeps offering new bargains.

How it works, step by step

  1. List the cost dials

    Model size, prompt length, retrieval depth, tool budget — each one moves the bill, and each one can be varied safely.

  2. Generate cheaper candidates

    The search tries combinations of those dials, guided toward the promising ones instead of testing everything blindly.

  3. Every candidate faces the gates

    Quality, speed, and reliability checks. A configuration that fails any gate is discarded — cheap is not an excuse.

  4. The cheapest survivor wins

    Among the configurations that pass everything, cost breaks the tie. That one becomes the recommendation.

  5. Savings are verified, not assumed

    Per-route cost tracking confirms the bill actually dropped where the change was made.

  6. The sweep repeats quarterly

    New models and providers keep arriving. Re-running the search keeps capturing the savings they offer.

What changes for you

Before, cost-cutting was a gamble: downgrade something, hold your breath, hope nobody complains. After, cost per workflow becomes a dial you can turn with evidence in hand, and the quarterly re-run keeps collecting savings as the market moves — without the quiet quality regressions that made everyone afraid to try. What it won't do: it won't shrink a bill whose real driver is volume. If usage doubles, this finds the cheapest way to serve it — not a smaller number of requests.