Fair question. Every AI visibility vendor claims results, so instead of asking you to trust ours, here is exactly what Aethon does and how to check it yourself before you pay anything.
Aethon maps the life moments people bring to ChatGPT, Gemini, Claude, and Perplexity in your category, tracks which brands each assistant recommends in those moments and why, and then executes the fixes: content, schema, citations, and coverage. Then it measures whether the recommendations changed. That loop is the product. The dashboard is where it starts, not where it ends. See how the platform works.
Run the test any honest vendor should survive. First, ask the four assistants the questions your buyers actually ask, in their words, and note who gets recommended. Our free automates this baseline in about a minute. Second, book the free audit call and we will run your brand live on screen, no slides. Third, re-run the same questions after the fixes ship and compare. AI models refresh on their own cycles, so changes take weeks, not hours, to show up.
No invented case studies, no fake star ratings, and no guarantee that a specific assistant will recommend you, because nobody controls the models. What we control is the input layer the models read. Pricing is published openly starting at $199 per month on the pricing page. If the baseline shows you already win every moment in your category, you do not need us, and the grader will tell you that for free.
Month one is baseline and fast fixes: your moments mapped, your current share measured across the four assistants, and the on-page layer shipped, direct answers, schema, fact alignment. Expect little answer movement yet; retrieval-layer changes need a refresh cycle to be read. Month two is where the first honest signal appears: moments where your evidence was close to threshold start naming you, and the citation plan begins landing third party mentions. Month three is when a program is judged fairly: the trend line across your frozen basket either slopes up or it does not, and because everything was baselined, you can attribute the slope to specific fixes rather than vibes. That cadence is not an Aethon quirk; it is how model refresh cycles and trust accumulation work everywhere, as laid out in why it is so hard to show up in AI.
Two situations produce weak results, and we would rather name them than surprise you. First, contested head terms with thin evidence: if your category's biggest moments are owned by brands with years of citations, three months of work narrows the gap but rarely closes it; the honest play is winning the specific and situational moments first while the trust layer compounds. Second, foundational problems marketing cannot fix: prices far off market, dead review profiles, or public trust damage will cap any visibility program, because assistants read the same evidence buyers do. In both cases the baseline conversation covers it before you spend, which is the point of the free audit call: fifteen minutes that occasionally ends with us saying you have a different problem than the one we sell to.
A note on why this page contains no customer logos or star ratings: we publish only what you can verify yourself. Vendor-selected testimonials are unverifiable by construction, so instead this site documents the method, baselines, frozen baskets, attributed fixes, and hands you the tools to run it on us, free, before and after purchase. As real platform runs accumulate, the plan is published aggregate data, share-of-voice movement across categories with the methodology attached, rather than curated quotes. If that standard reads as unusual for a marketing site, that is rather the point: a company selling verifiable AI visibility should be the easiest vendor in your stack to audit, and the measurement discipline in how to know if your GEO is working is the same one we invite you to point at us.
Baseline visibility appears the day you run it. Changes in what assistants recommend typically take weeks because models refresh their reading of the web on their own cycles.
No, and no honest vendor can. Aethon controls the inputs assistants read: moments coverage, content, schema, and citations, then measures whether recommendations change.
Yes. The free GEO Grader shows how visible your brand is to ChatGPT, Gemini, Claude, and Perplexity in about a minute, and the free audit call runs your brand live with a specialist.
A complete baseline, the input layer shipped, and a rising trend in the moments closest to your product. Broad head-term wins take longer everywhere, and anyone promising them in weeks is guessing with your budget.
Frozen question basket, before and after answers, and the cited sources for each change. When a fix ships and the moment flips with our fix among the sources, attribution is direct; when it is ambiguous, the report says so.
Yes, and the grader does it automatically: if your baseline shows you already winning your category's moments, we say maintenance is all you need, and what maintenance looks like is documented on this site for free.
Because unverifiable proof is not proof. The free baseline and the frozen-basket method give you evidence about your own category, which beats any story about someone else's.
Aggregate, methodology-attached data from real platform runs is the roadmap for public proof, in place of curated testimonials. Until then, the verification test above is the honest offer.