The measure
everything else
is built on.
The Trust Index is how we see what AI really says — about a brand, a category, a market — and how much humans actually believe it. It’s the research that led to our method and our agent. And it’s where every engagement starts.
Three things AI decides about every brand.
Findable
Do you appear when buyers ask AI, or not at all?
Accurate
Does AI get who you are and what you do right?
Recommended
Does it name you, or hand the customer to a competitor?
The Trust Index measures all three, on the questions your buyers actually ask.
Two ways to get the answer.
Ask Taylor
Self-serve snapshot in about two minutes. $47. Findability score, who AI names instead, accuracy flags — single-pass, scope declared, human-reviewed before it sends.
For: "just show me."
The Trust Index diagnostic
Run by our team: 20 prompts, multi-pass with median scoring, four pillars, competitive read, and a sequenced fix map. Scoped to you on a call.
For: "show me everything, then tell me what to do."
Same method. Same honesty. Different depth.
What you walk away with.
We run the questions buyers ask in your category and market across the major AI engines, and score what comes back with a versioned, repeatable method. Plain-language findings — and the sequence to fix them.
Scores with their scope declared
Prompts, engines, date. Every number carries its scope; that's the discipline.
Who AI names instead
The competitors and directories taking your answers today.
Accuracy flags
Anywhere AI confuses you with someone else, or gets your market or category wrong.
The gap-to-fix map
Every finding tied to the CitationStack phase that addresses it.
Built on real field research.
The Trust Index isn’t only about machines — it’s about whether people believe them. We interview strangers on camera about how much they trust what AI tells them: 44+ unscripted interviews so far, filmed in Toronto, with New York, Seoul and Busan in progress. The average so far: 4.9 out of 10 — people trust AI for facts they can check, and hesitate on judgments they can’t. That hesitation is exactly where brands now live.
The 4.9 is research context — it never appears in any client's score.
44+
interviews · filmed in Toronto · expanding
The measure came first. Everything else followed.
Measuring thousands of AI answers taught us what the engines actually reward — and that became CitationStack 200™, the sequenced method. Running the measure at scale needed an operator — and that became Taylor, our AI agent with a human approving every move. Audit → method → operator. Same discipline end to end: measure honestly, declare the scope, fix in sequence.
CitationStack 200™
200 sequenced actions that build the mentions, reviews, and content AI trusts, run in order.
Trust Index™
Where every engagement starts — scores with their scope declared, and the sequence to fix them.
Taylor AI
Maps the prompts buyers use, finds the gaps, and ships the fixes, with a human on every move.
Trust research, commissioned.
Organizations also engage the Trust Index directly — to understand how AI systems represent their market, their category, or their region, and how public trust is shifting. If you need to know what AI says about a space you care about — and whether people believe it — that's a conversation we'd enjoy.
The questions agencies actually ask.
We already rank on page one. Why doesn't AI recommend us?
We already rank on page one. Why doesn't AI recommend us?
Where do the scores come from?
Where do the scores come from?
Is the 4.9 my score?
Is the 4.9 my score?
Do you guarantee results?
Do you guarantee results?
How often should a brand re-measure?
How often should a brand re-measure?
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Start with the measure.
You can't fix what you haven't measured — and measurement starts at $47.
CitationStack 200™ is the white-label engine that makes AI cite your clients. You stay the expert; we stay behind the scenes.