Is Your AI Bill Bigger Than It Needs to Be?
One week. Fixed price. A written report on where your model spend goes, what you can cut without your users noticing, and how to move to newer models without breaking what works. For teams with AI already in production. If you go ahead with the changes, the fee comes off the price.
Technology Partners
Recognized by Clutch
AI Cost and Model Review
One week. A written report plus a call. Credited in full against the work if you engage us within 90 days.
What the Report Contains
The same six sections every time. The price is fixed, so the shape is fixed. A section with nothing to fix is a finding too, and it gets written down.
What you spend, and on what
Your model bill broken down by feature, model, customer and tool call, ending in a cost per task: what one support answer, one document processed or one agent run actually costs you today. Most teams know the monthly total and very little below it.
Where the money goes that does not need to
Ranked by monthly saving, biggest first. Prompt caching, context that gets sent and never used, the wrong model for simple steps, retries, work that could run through a batch API, and self hosting where the volume justifies it. Each item comes with an estimated saving and the quality risk of making the change.
Whether you can change models safely
A cheaper or newer model is only a saving if quality holds. We check what evaluation you have. If there is none, we build a small evaluation set from your own traffic during the week, so every change in the report can be tested before it ships.
Which model deadlines apply to you
The models you depend on that are scheduled for retirement, the dates, and the newer models worth moving to, with what each move is likely to do to cost, latency and quality on your workload.
What the changes cost and how long
A scoped plan for the changes worth making, in days of engineering, set against the monthly saving each one buys. Some changes pay back in a week. Some never do, and the report says which.
A proposed first milestone
If you go ahead: what gets changed first, by when, and the numbers that tell both sides it worked, written as a target cost per task at a quality score you agree in advance.
Why This Exists
The first version of an AI feature is built to work. Nobody tunes what it costs, because there are no users yet. Then usage grows, the bill grows faster, and the system that was fine at a hundred requests a day is now a line item someone in finance asks about.
At the same time the models underneath keep moving. Providers retire versions on a schedule, and new models arrive that are cheaper or better at your task, sometimes both. Switching without a way to measure quality is a gamble, so most teams stay where they are and keep paying.
A week is enough to find out what each request costs, where the waste is, and which changes are safe. You can make them with us, with your own team, or with someone else.
Still on a prototype? The Production Readiness Review is the same price and the same shape, aimed at getting a product ready for its first real users.
What We Need From You
Four things, all of them on day one. The week starts when the last of them arrives, not when you sign.
- Read-only access to your model provider usage and billing (OpenAI, Anthropic, Bedrock, Vertex or Azure)
- Read-only access to the code that calls the models
- Traces or logs if you have them (Langfuse, LangSmith, Datadog or similar), or a sample of real requests
- A 45 minute walkthrough call, plus your written answer to: which features matter most, and what quality is the minimum
Questions
Start With a Call
Thirty minutes, no charge. Tell us what you run and roughly what it costs. We will say whether the review is worth it at your volume, and say so plainly if it is not.
Or Send Us the Details
Which models you use, roughly what you spend each month, and what worries you about it. We reply within 24 hours.