FinOps for AI · invite-only design partner program

Know what every LLM call costs.
Prove what it should cost.

Strata is an observability and optimization proxy for your LLM traffic. It sits inline, attributes cost to every app, user, and call, and runs experiments on your own production traffic to find cheaper models that hold quality — with the evidence to prove it.

Request an invite See how it works
One bill, three strata
per appsupport-bot · $412.18 today
per userteam-acme · 3,208 calls · $96.40
per call$0.0041 · 1,204 in / 312 out
How it works
Observe. Experiment. Save.
Strata sits between your code and your model providers. The calling contract never changes — the economics underneath do.
01 · observe
Every call, priced
Drop Strata in front of your existing endpoints. Each call is traced and priced in real time, so spend breaks down per app, per user, per call — instead of arriving as one opaque invoice.
02 · experiment
Your traffic, replayed
Strata samples real calls from production and replays them against candidate models inside a budget you set. An independent judge scores quality on both sides — no synthetic benchmarks.
03 · save
Savings, with receipts
When a challenger beats the incumbent on cost with quality held, you get a recommendation backed by the full evidence chain. You approve it — Strata never reroutes on its own.
recommendationtask: support-summarize
incumbent · large-generalquality 0.86 · $0.0041 / call
challenger · small-tunedquality 0.87 · $0.0016 / call
projected savings −61%awaiting your approval
Why Strata
Your AI bill, made answerable
Model spend is now a line item finance asks about. Strata gives you the answer — and a defensible way to shrink it.
Cost visibility per app, per user, per call
Every call is priced from live provider rates and attributed to the app, user, and feature that made it. Spend stops being a monthly surprise.
Experiments on your workload, not benchmarks
Public leaderboards don't price your prompts. Strata evaluates candidate models on calls sampled from your own production traffic, within a capped experiment budget.
Provable savings
Every recommendation carries its evidence: the sampled calls, the judged quality scores, the cost delta. Take it to finance as a receipt, not a guess.
You stay in control
Routing changes only when an operator approves them, and every change keeps its full audit chain. No silent model swaps, ever.

Working on your AI spend?

We're onboarding a small group of design partners. If your LLM bill is a number someone keeps asking about, we'd like to talk.

Get in touch
invite-only while we build with early partners