When someone asks an AI about your category, does it name you, or your competitor?
Your customers stopped typing searches and started asking ChatGPT, Perplexity, and Google's AI Overview. The answer they get back either names your brand or it does not, and right now you have no idea which. GEO / AI-Answer Visibility is rank tracking for the answer instead of the page, it measures whether you exist inside the generated answer at all, how your share of voice compares to your competitors, and what content would move you up.
See whether AI answers name your brand Run a sample GEO report
THE PROBLEM
For a decade you earned the click, you ranked the page, you tracked the position, and the whole industry built tools to tell you exactly where you sat on the results page. That surface is quietly draining. When a buyer asks an answer engine about your category, they get a synthesized answer that names a handful of brands and cites a handful of sources, and increasingly they never click through to a results page at all. If your competitor is the one the model names, you lost the customer before you knew there was a race, and none of the SEO tools you already pay for can see it, because they measure the page, not the answer. The surface that is replacing the one you track is the one nobody is measuring.
HOW IT WORKS
BEACON runs a fixed set of the category questions your buyers actually ask through the same kind of answer generation an engine uses, then reads each answer the way an auditor would. It extracts who got named, who got cited, and in what order, and it scores your brand's citation share and your share of voice against a competitor roster you define. Then, in the same sweep, Kendra's content engine drafts the gap-fill content in your voice for every prompt where a competitor got cited instead of you. The scoring over the answer is deterministic, the only model call is the answer generation itself (exactly the step an answer engine performs), and everything that shapes the run, the prompt set, the competitor roster, the citation rubric, the cadence, lives as configuration you can edit, not code you have to rebuild.
WHAT YOU GET
- A per-prompt visibility report, does the AI name you, cite you, rank you, or skip you
- Citation share and share of voice, scored against the competitors you name, tracked over time
- The gap-fill content drafts, in your voice, for the prompts where a competitor won the answer
- A trend line, so you can see whether your answer-surface presence is climbing or eroding
- A structure that extends cleanly, a new answer engine or a new scoring rubric is a config edit
WHO IT IS FOR
Marketing and SEO leads watching organic clicks erode with no instrument for where they went. Content and comms teams whose buyers now research through AI answers before they ever hit a site. Founders wearing the growth hat who need to know, this week, whether the AI names them or the competitor. It is not for brands with no organic-discovery motion, or teams that only run paid.
PRICING
Pricing is a set of hypotheses we are validating in the open, not a committed rate card, and the idea is to price the ladder rather than a single number.
- Monitor, the always-on instrument, a recurring GEO report on a fixed prompt set and competitor roster. Hypothesis: around $199 per brand per month. - Monitor plus content, the report plus the in-voice gap-fill drafts produced in the same sweep. Hypothesis: around $499 per brand per month. - Agency, multi-brand command for teams running the answer surface for a book of accounts, value-metered and negotiated.
Every paid step is gated, a charge never happens without an explicit confirmation.
PROOF (the dogfood)
AYA runs BEACON on itself. The prompt set is the set of questions a buyer would actually ask an answer engine (best AI agent framework, tools to verify what an AI produced, AI compliance verification), the competitor roster is AYA's real comparables, and the sweep reports whether the answer names AYA or something else, then drafts the content to close any gap. We eat exactly the instrument we sell, and the product's own build already left a receipt, the deliverable pattern was quality-scored (84 out of 100, grade B) and all five of the capabilities it composes were verified on disk before this page was written.
HONEST NOTE
Here is what is true and what is not yet. The measurement structure is built and verified, and the scoring over an answer is deterministic. What is not yet done is a live run against a real third-party answer engine, today the self-check generates the answer through AYA's own model lane, which is a reasonable proxy for what ChatGPT or Perplexity would say, but it is a proxy, not the same thing. Measuring genuine ChatGPT, Perplexity, or AI-Overview output needs either a live answer-engine connection or the SERP scraper we already have, plus funded keys, and we have not run that yet. So we will not put a real citation-share number in front of you and call it a ChatGPT result until we have actually measured ChatGPT. No live run, no real answer-engine data, and no spend happened in building this, and the prices above are hypotheses we intend to test with you, not settled numbers.
*This page is a specification. The capability it describes is not built yet, and nothing here is a claim that it runs today.*