AI became a real cost before anyone built the tools to manage it.
Every other major cost in a business arrives with decades of management practice attached. This one arrived in eighteen months, and finance was handed the number without being handed anything to do about it.
Why does Camaze exist?
Because AI cost tooling was built for engineers, and engineers are not the ones who have to explain the number. Existing tools organize around traces, prompts and latency, and assume the reader can interpret a log. Finance needs something that starts from the bill and speaks in budgets, owners, variance and forecasts. Camaze is that, built in the opposite direction from everything else in the category.
What we believe
Three things, and they shape most of the product decisions.
The wedge is finance, not engineering
Engineers are not measured on the cost line, so tools built for them treat cost as a secondary panel. Finance is measured on it and has had nothing. Building for finance means starting from the invoice, not from the trace, and it changes almost every design decision downstream.
The point is to spend more on AI, not less
AI budgets get frozen when nobody can explain them. A cap is the only responsible response to an unexplained cost, and it lands on the work that was paying off along with the work that was not. Removing that uncertainty is what makes expansion approvable.
Specific beats comprehensive
A maturity score is not useful. A finding that says a named workflow is spending a specific amount on a frontier model doing classification, and that a smaller model would recover most of it, is useful. Every recommendation carries a dollar figure and an owner or it does not ship.
What we kept seeing.
A company starts with one API key. A year later it has several providers, cloud-routed access to some of the same models, open-weight models on rented GPUs, coding assistants on per-seat contracts and a handful of AI tools bought on cards. Each decision was reasonable. Nobody has the total.
Then the questions start arriving. What did AI cost last quarter. Which product does it belong to. Why did it jump in March. What does it cost next year. What did we get for it. These are ordinary questions about any material cost, and for AI they are close to unanswerable in most companies.
The consequence is not usually a crisis. It is a quiet cap. AI spend gets limited because it cannot be defended, and the limit is applied without the information needed to apply it well.
Most companies find they can get the same AI output for roughly half the cost. That means the constraint is almost never real. It is an information problem being solved with a budget instrument.
Some commitments.
Read-only, always
Nothing we connect to can spend money, change a deployment or read your prompts and completions. Out of band, never in the request path.
No invented numbers
Estimates are labeled as estimates. Apportioned figures are labeled as apportioned. Realized savings are verified against actual spend rather than assumed from a projection.
No success fees
Flat pricing, because a percentage of savings creates an incentive to inflate what counts as a saving. See pricing.
We will tell you if it is not worth it
If the savings available at your spend level do not justify the fee, we would rather say so on the first call than sell a pilot that disappoints.
The details
Team, funding, location and customer details are placeholders.
We have deliberately not published a team page, an investor list, customer logos or case studies, because none of them exist yet and inventing them would contradict the point above about not making numbers up. Every placeholder on this site is listed in the project's PLACEHOLDERS.md file.
If you want to know who you would be working with, ask on the demo call and you will get a straight answer.
Questions people ask
Who is behind Camaze?
Team details are being finalized and will be published here shortly.
Are you hiring?
Open roles will be listed here. In the meantime, if you have built finance systems or worked inside an FP&A function and this problem is familiar, write to hello@camaze.com.
Where are you based?
Company location and entity details will be published here.