AI spend, made accountable
Who spent it, what it was for, and what it should have cost. A monthly AI statement your finance team can read, question and act on, without a single acronym.
Why we built RouteMeld
Mike wanted to see exactly how his own people were using AI, so he bought a laptop and did the work himself. He hit usage limits, upgraded, hit them again, and upgraded again. Then he asked the question every executive should: if one person can spend like this, what happens when thousands do, and where is all that data going?
Use the flagship models for the tasks that genuinely require them.
If a member of the HR team uploads a document for analysis that contains employee information... the data stays inside your perimeter.
If you imagine thousands of developers at a Fortune 500 company all doing what I was doing on my own, where is that data going?
Quotes from Mike Hiltz on The Cyber Business Podcast, Ep 225 (CyberLynx, July 2026), lightly trimmed.
Where the savings come from
Most AI spend goes to sending too much, to a bigger model than the job needs, at full price. Every saving comes with a receipt finance can check.
Illustrative prices. Your receipts use your providers' rates.
Your AI bill, decoded
No computer science required. Each one explains a line on your bill.
You pay for every word sent to the AI and every word it writes back. Ask six follow-up questions about a 40-page contract, and the whole contract can be billed six times.
AI providers sell several models at very different prices. The top models often cost ten times or more per word than smaller ones, and most everyday work doesn't need them.
AI agents don't answer one question. They read whole folders, call tools and check their own work in loops. One engineer with an agent can spend in an afternoon what a team spends in a month.
Copilot and ChatGPT seats are a fixed monthly cost, whether people use them or not. API usage is a meter that keeps running. Most companies pay for both, and few track either against what it delivers.
Free guide
A short, plain-English guide to what your company is spending on AI, where the money goes, and how to bring it under control. Written for finance and operations leaders, not engineers.
We'll email the guide and nothing else unless you ask. No spam, no sharing.
In plain English
Who's behind it
CISO and CIO in healthcare AI, including carrying a medical device through FDA 510(k) clearance. Army Ranger before that.
CISSP · CISM · CIPM · AIGP
Two-time CISO and four-time CIO, building and scaling security and technology programs across regulated industries.
SOC 1 · SOC 2 · ISO 27001 · HITRUSTWe read the bills and usage your providers already report, inside your environment, and hand you one page: who spent what, on what, and what it should have cost.
Review notes · not part of the page
It plays right on the page from your 24:50 segment and stops around 28:00. On the live site we'd load the player only when someone presses play, from YouTube's privacy-enhanced domain. Embedding the public video is fine; cutting our own clip would need CyberLynx's OK.
They come from CyberLynx's published transcript, which is lightly edited. Can you check them against what you said and approve the trims?
The page doesn't name nference, so it won't read as a customer or an endorsement. Let's confirm you're comfortable being featured this way.
In July you described catching prompts before they leave the network. The site today says we read the bills. The quotes work for both, but the data quote implies routing. Let's agree how much to promise.
You said: "We have to get better at tying security investment to business outcomes." That's the business-first idea in your words, and could open the founders section.
The form is a placeholder on this draft and doesn't send anything. We'd need to write the guide (4 to 6 pages, both our names on it) and connect the form to the same backend as the early-access form, with a short privacy line.
