About
Our work starts on the invoice. We baseline what production actually costs per successful outcome, then move only the workloads that pay for the move.
Protecting your margin
as AI usage scales
Stop cost growth
before it tracks revenue
Inference billed per token grows with usage, not with margin. Left alone, a working feature turns into the largest line on the infrastructure invoice.
Protect output
quality under change
Every routing or model change is measured against a company-specific evaluation set. A change ships only after it clears the quality floor on real traffic.
Own the system
after the engagement
Evaluation sets, routing policy, and runbooks stay with the client team. The work is transferable on purpose, not dependent on a retainer.
Key economics after one bounded production change
54%
quality within one point
Where the traffic ends up after routing
Cost per successful outcome
93% classification accuracy
on a hosted 8B model
Invoices, usage exports, and traces joined to task-specific quality results — so every recommendation carries a number next to it.
Case study
Series B support automation platform · Ticket triage and resolution copilot
Per-resolution cost fell 54%. Quality held within one point of baseline across 12 weeks of production traffic. The client's platform team took over the routing policy and evaluation set. They run it without external support.
Start with the bill, not a brainstorm
Bring 60 to 90 days of invoices or usage exports, one representative production workload, and the decision you need to make.
We take on two to three engagements per quarter.