AIRANKS — The Authoritative Rankings for AI Web Content

AIRANKS measures AI visibility: we ask AI models real product and service questions, capture the complete answers as immutable observations, and publish what they contain — which brands were mentioned, which domains were cited, and which exact pages were linked. Every domain gets an AIR score from 1–10 (a decile of visibility in the active dataset; 0 means insufficient data), with the methodology in the open.

The live ledger — phrase, brand, and domain rankings
Methodology — how observations become scores
Domain reports — any site's AIR score, Machine summary, and AI-file audit
llms.txt and llms-full.txt — the curated index for AI readers
Public API — domains, brands, phrases, search
Blog — the build log

About AIRANKS

AIRANKS measures how often and how favorably brands show up in the Machine's own answers — not SEO proxies, not guesses. Every score carries a confidence interval, because a single number without one is a claim, not a measurement. AI Rankings: measured, not guessed.

Leadership

Jeremy Schoemaker

Founder

Jeremy Schoemaker was one of the first people to write about search engine optimization in public, starting in 2003, and entered SEO contests against agencies many times his size — and won. He'll entertain a dozen theories about why something ranks or converts, but he only trusts the one that survives an actual measurement. That instinct built two companies bought out from under him — AuctionAds (acquired 2007, $17M) and PAR Program (acquired 2015, $12M) — and it's the same instinct behind this site. He is the author of Nothing's Changed But My Change: The ShoeMoney Story, and today works hands-on building the AI/LLM infrastructure — the agents, evaluation harnesses, and model plumbing — behind AIRANKS itself.

a quick ledger of his own

writing SEO publicly since: 2003
single-month AdSense check: $132,994.97
eBay Star Developer Award: 2007
AuctionAds, acquired: $17M
PAR Program, acquired: $12M
conference talks, incl. 4 keynotes: ~55

Why Measurement

SEO in its early years ran mostly on folklore — theories passed hand to hand at conferences, rarely tested against results. Schoemaker's approach was different: run the experiment, read the numbers, keep what held up and drop what didn't. That's how a small operation kept beating firms with far more headcount.

AIRANKS applies the same standard to a newer question: whether a brand actually shows up in what AI models say, and how much that answer can be trusted. Not a ranking pulled from search position or backlinks. Not a theory about how a model probably behaves. A measured count, repeated enough times to know whether it's stable, with the interval shown next to it — because a number without one is a theory, not a result.

What We Do

AIRANKS captures real answers from the Machine across a running dataset of phrases, then scores brand visibility from what actually came back — never inferred from search rankings or backlinks. See the full method on the Methodology page and the rules we hold ourselves to in the Constitution.