Compare lower-cost and premium model configurations on real customer workflows to learn where additional model quality creates detectable customer value.
Across the sponsor's highest-volume workflows, 63% of production requests met predefined task-success and customer-preference equivalence on the lower-cost model; the remaining task classes stayed on premium.
You get a workload-by-workload routing map: which requests can move down-tier, which customer segments notice the difference, and the resulting blended unit economics.
Down-tier the eligible traffic and keep premium inference only where the measured customer-value gap justifies it.
If the intervention does not clear the predefined threshold, that is evidence against spending more to build, launch, or scale it in this context.
Retain premium inference for those tasks.
If the intervention clears the threshold but the business keeps the current approach, measurable savings, revenue, adoption, or risk reduction may remain unrealized.
Act only when the measured opportunity is large enough to justify the change.
On sponsor-defined routine workloads, a lower-cost model configuration will match the premium configuration on task success and customer preference within predefined equivalence margins while reducing serving cost by at least 80%.
Serving cost per successfully completed, customer-preferred task.
No more than 2 percentage points lower task success, no more than 5 percentage points lower customer preference, and at least 80% lower serving cost.
Evidence for where cheaper inference can replace premium inference without sacrificing customer-visible value.
Route the tested workload to the lower-cost configuration.
Use selective routing by workload.
Retain premium inference for those tasks.
Business outcomes are research targets, not guarantees. A null or negative result may still create substantial value by preventing investment in an ineffective product, feature, or campaign.
Current or prospective customers completing representative sponsor-defined workflows.
A lower-cost model or inference configuration selected for routine task classes.
The sponsor's premium model or inference configuration on the same tasks and interface.
Task success · Customer preference · Latency · Escalation rate · Willingness to pay
We adapt the population, intervention, thresholds, and economics to your customers. The result may tell you to scale, to stop spending, or to act on an opportunity you are currently leaving unused. Each of those is a useful business decision when the evidence is strong enough.
The goal is not a positive result. The goal is evidence strong enough to change a real decision.