Your AI bill, taken apart line by line.

The AI Cost Audit is a fixed-scope review of your AI usage, model choices, and architecture. You get a written report that names the waste, the risk, and the fixes. Each finding comes with a dollar figure. Two weeks, one price.

Book a free intro call →

15 minutes to see if this fits. No pitch if it doesn't.

Why It Pays For Itself

Most AI bills carry the same problems.

Expensive models doing work a cheaper model handles fine.
No caching, so you pay full price for repeated work.
Real-time API calls for jobs that could run as batch at half the price.
Commitments and reservations that don't match how you actually use them.

If your team spends $10,000 a month or more on AI, finding one of these usually covers the fee. Finding two or three is common.

What You Get

A report your team can act on the same day.

A spend map. Where the money goes, by model, feature, and workload.
Findings with dollar figures. Every problem priced: what it costs you today, what it costs after the fix.
A ranked fix list. Ordered by savings against effort, so your team knows what to do first.
Risk flags. Commitments, rate limits, lock-in, use-it-or-lose-it capacity.
A 60-minute readout call with your team to walk through all of it.
The report ships as a clean markdown doc. Your engineers can hand it straight to their own AI tools and start fixing.

How It Works

Three steps, two weeks.

Free intro call (30 min). You tell me what you're building and roughly what you spend. I tell you whether an audit is worth it for you, and exactly what to send me.
You send three things. Usage and billing exports from your AI providers (last 30 to 60 days), a list of the models you use and what they do, and an architecture sketch or a 30-minute walkthrough with one of your engineers. Read-only exports. I never need access to your production systems.
Two weeks later: the report and the readout call. Done.

Who This Is For

The person who owns the AI bill.

Founders, CTOs, platform leads, FinOps leads. Teams spending roughly $10,000 a month or more on AI APIs and infrastructure.

Not for you if: you're still exploring AI and the spend is a couple of subscriptions, or you want someone to rebuild your stack for you. I advise. Your team owns everything.

Who I Am

I do this work every day.

Saurav Sharma. Six years at Amazon. 12 AWS certifications. I was doing this work on cloud bills before AI bills existed: finding cost and architecture problems in enterprise AWS accounts as a Senior TAM. Now I do it for AI spend every day: model selection, commitment math, caching and batching, the pricing fine print across OpenAI, Anthropic, Azure, and AWS. I teach 30,000+ students on Udemy and run the CloudYeti YouTube channel.

What Happens After

The audit comes first. Everything else comes later.

Most teams keep me on for a quarterly review, because model prices, commitment options, and the cheapest way to run a workload change every few months. Some bring me into their sprints as an advisor. If the audit shows your team needs it, I also run a hands-on workshop. All of that comes later. The audit comes first.

FAQ

Common questions.

Do I need to give you access to our systems?

No. Read-only billing and usage exports, a model list, and an architecture sketch. That's it.

Will you sign an NDA?

Yes.

What if you don't find anything?

Then you get written confirmation that your setup is sound, plus the specific things to watch as pricing changes. Teams that pass clean are rare, but that answer has value too.

Do you implement the fixes?

Rarely, and only when a fix needs a real build. The report is written so your team can act on it. If you want ongoing help, that's the advisory retainer, and we talk about it on the readout call.

We spend less than $10K/month. Can we still work together?

Probably the better fit is a paid 1-on-1 hour where we go through your setup live.