The AI Cost Audit is a scoped 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. The price is set after we agree on the workload boundary.
Book a free intro call →15 minutes to see if this fits. No pitch if it doesn't.
If your team spends $10,000 a month or more on AI, one good finding can usually cover a starter audit. Larger estates need a larger scope, because the work grows with the number of workloads, providers, accounts, and stakeholders involved.
The $2,500 starter audit covers one AI product or workload, one team, up to two providers or accounts, a written report, and one readout call.
One bounded workload or product area. Good when the spend is real, but the surface area is still narrow.
Multiple workloads, teams, providers, accounts, or commitment decisions. We set the boundary before any data moves.
Large estates, business units, procurement questions, exec readouts, or phased delivery. The work is priced to the estate, not squeezed into the starter box.
I price the audit by surface area, not as a percentage of your bill: workloads, providers, accounts, stakeholders, commitment math, and how many readouts or report versions your team needs. You know the price before you send data.
Founders, CTOs, platform leads, FinOps leads. Teams spending roughly $10,000 a month or more on AI APIs and infrastructure, or larger organizations trying to understand which AI workloads are worth more spend.
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.
Saurav Sharma. I’m a cloud and AI cost optimization consultant. I help companies understand where their AI spend is going, what business value it is creating, and which parts are worth optimizing.
My background sits across both sides of this problem. I spent 6 years at Amazon, first working with large enterprise customers as a Senior Technical Account Manager on cloud architecture, cost optimization, reliability, and scaling, then building LLM and GenAI platforms as an engineer.
I also spend a lot of time teaching this space. I hold 12 AWS certifications, teach 30,000+ students on Udemy, and run the CloudYeti YouTube channel.
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.
15 minutes to see if this fits. No pitch if it doesn't.
No. Read-only billing and usage exports, a model list, and an architecture sketch. That's it.
Yes.
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.
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.
By scope. A single bounded workload can fit the starter audit. Multiple workloads, providers, accounts, business units, executive readouts, or procurement decisions become a larger scoped audit. I quote that on the intro call before you send data.
Probably the better fit is a paid 1-on-1 hour where we go through your setup live.