Precision token forecasting
Stop curve-fitting the past to predict your AI spend.
Price the future with TokenWake.
Today's models. Today's pricing. Today's performance.
Powered
by the only math that sees your costs cascading before they do.
Worked scenario
An AI budget built to last twelve months. It lasted four.
That happened in 2026, to a large engineering organization, and it is public record. We modeled the shape — 5,000 engineers, adoption doubling in a month — and let TokenWake price it.
- $2.2M in four months, still accelerating. Draw any budget across that curve and you get the date it breaks.
- A spending cap bought 23 days — and stopped 20,459 sessions mid-work. The budget still ran out.
- Same cap, different models — the spend came inside the budget, with no change to volume or behaviour.
That is the answer TokenWake computes.
A modeled scenario, not a prediction.
The category
The whole category measures. We forecast.
There are good tools in this market and they are well funded.
Not one of them prices work that hasn't happened yet.
| TokenWake | Everyone else |
|
|---|---|---|
| Reports past spend | — | ✓ |
| Curve-fits past spend | — | ✓ |
| Enforces a cap | — | ✓ |
| Prices a cap | ✓ | — |
| Forecasts before you build | ✓ | — |
| Recommends a configuration | ✓ | — |
| Diagnoses structure before build | ✓ | — |
Everyone else is
looking backwards.
Result?
The first solid number you see is an invoice.
Everyone else is FinOps platforms, observability and tracing, gateways and proxies, spend management, and each provider's own rate card — CloudZero, Langfuse, LiteLLM, Ramp and the rest.
Category comparison as of July 2026.
How it works
A wind tunnel for your workflows.
We build your workflow and run it — work arriving, failing, being retried, queueing behind a reviewer — tick by tick, for as long as you ask, before any of it is deployed.
Not a curve fitted to last year's invoices. Everything else extends a line drawn through spend that already happened — which is no use at all for a workflow that has never been run.
- Nothing takes turns — retries, queues and rework all move while everything else is moving, so you never have to know in advance which interactions matter.
- 100% deterministic and reproducible — the same inputs replay to the same numbers.
- Grounded in independent benchmarks — model performance comes from Artificial Analysis, not vendor claims: hallucination rate, accuracy, agentic success rate, latency, and coding score.
- Ends in a recommendation, not a dashboard — every model is scored in every position on your workflow, and we name the ones to run at each step, with the shortlist behind them.
What you get
One workflow in, three answers back.
All three come out of the same run, for one price.
01 Token forecasting
What your workflow will cost
What the workflow will cost before you deploy it — derived from its structure, not fitted to a usage history you don't have yet.
02 Model selection
Which models to run, step by step
We name the configuration to run — every model scored in every position, ranked by true cost per delivered task rather than sticker price. In a 196-configuration sweep of a draft-and-validate flow, the cheapest by API price came dead last — 5.25× the true cost of the winner.
03 Workflow diagnostics
Where the money goes
Steps that burn budget looping on their own output — and workflows with no spawning limit, which we cannot forecast unless you put a cap on them.
The example is a staged scenario with no relation to any real company — the intake came through this form as a pipeline test. The figures are genuine output from a certified twelve-month engine run, and every heading, table and caveat is what a customer receives. This is one workflow. For an organisation running many, there is an enterprise-level summary covering recommended configuration and cost behavior by type of work — ask us for it.
Send us one workflow
Price it before you build it.
What your workflow will cost, the most cost-effective configuration,
and where the money goes.
$15,000 introductory offer · $1,000/mo model refresh.
Know the cost before the token spends.