Features · Free layer

Public leaderboards — the ranking you can't buy

We ask four AI engines the real buyer questions in a set of categories and publish who they recommend — free, indexable leaderboards built from measured snapshots, re-run periodically, with a confidence interval on every rank. No signup, no email gate, and no way to pay for a position. CiteGraph appears on its own category's board, ranked last, because that's where the measurement put us.

How it works

01

Real questions, repeated runs

Each category runs its buyer questions across 4 engines with repeated runs per question. Every snapshot is dated and kept, so a board's history is a genuine time series.

02

Entities resolved before counting

Tiers, renames and spelling variants fold into one product before anything is ranked — the same alias resolution the product uses — so no brand is split into three rows or counted twice.

03

Ranked with intervals, tied when tied

Every rank carries a Wilson confidence interval. Brands whose intervals overlap are shown as statistically tied rather than fake-ranked — at these sample sizes, that honesty is the difference between a measurement and a listicle.

In depth

Why it's free

The boards are the public proof of the method the paid product runs on your own domain. Giving the category-level view away costs us scan spend and earns the thing no ad can: a ranking whose integrity is checkable.

Why rank can't be bought

There is nothing to buy — rank comes from counting engine answers, the method is published on the methodology page, and anyone can reproduce a board by asking the same questions. We rank last in our own category and publish it anyway; that's the guarantee working.

Per-engine disagreement, visible

The boards show each engine's view separately — and they disagree more than anyone expects. In our measured categories, two engines' top-5s have shared as few as 2 of 5 brands. Any tool reporting one blended number is averaging away the finding.

What we won’t claim

What we won't do: sell placement, accept “corrections” from vendors, or quietly re-run a board until it flatters someone. When our own product ranks last, it stays published. A leaderboard is only worth publishing if nobody — including us — can put a thumb on it.

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Common questions

Which products do AI assistants recommend most?+

It depends heavily on category and engine — which is the finding. CiteGraph's public leaderboards measure it per category across 4 engines, with a confidence interval on every rank and each engine's view shown separately. They're free and require no signup.

Can a company pay to rank higher?+

No. Rank comes from counting what engines answer, the method is public, and anyone can reproduce a board. CiteGraph itself ranks last in its own category's board and we publish that.

How often are leaderboards updated?+

Boards are measured snapshots, re-run periodically — each one is dated on the page, and every snapshot is kept, so a board builds a real history of how AI recommendations in that category shift.

Why do the engines disagree with each other?+

Different retrieval, different source preferences, different synthesis. In our measurements, per-engine top-5s have overlapped by as little as 2 of 5 brands for the same questions — which is why the boards show each engine separately instead of blending them.

See it on your own domain — first dossier in about a minute.

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