Solution
Control how AI describes your brand
Millions of buying conversations now start with an assistant. What it says about you when nobody's watching is your brand narrative — and unlike a press release, you don't get to write it.
AI answers are a reputation surface with no editor to call. An assistant will confidently characterise your brand based on whatever it retrieved: a two-year-old review, a Reddit thread, a competitor's comparison page. Sentiment and framing analysis tells you what that characterisation actually is, per engine, over time.
What makes this hard
The specific problems this creates — not generic advice about “the AI era”.
Outdated narratives persist
A pricing complaint from three years ago can still shape how an assistant describes you today, long after you fixed the pricing.
You don't control the sources
Assistants cite forums, review sites and news. Your owned content is one voice among many, and often not the loudest.
Crises move faster than monitoring
Traditional media monitoring catches articles. It doesn't catch an assistant repeating a negative framing to every person who asks about you.
The questions your buyers are actually asking
Reputation prompts are the ones nobody thinks to track until something goes wrong. They're also the fastest way to discover that an assistant is repeating something outdated or simply untrue about you.
- “Is [your brand] trustworthy?”
- “What are the main complaints about [your brand]?”
- “Has [your brand] had any controversies or security issues?”
- “Is [your brand] better than [competitor] for enterprise use?”
- “What do customers say about [your brand]'s support?”
Replace the bracketed terms with your own. Every one of these returns a different answer depending on which assistant you ask.
What to measure
The metrics that matter for this work, and why each one earns its place on a dashboard.
Sentiment by engine
Assistants disagree. One may be neutral while another repeats a negative framing.
Framing analysis
The adjectives attached to your brand — 'affordable', 'complex', 'dated' — shape perception more than presence does.
Source classification
Whether assistants lean on your owned content, news, reviews or forum threads.
Sentiment trend
A gradual drift matters more than a single bad answer, and only shows up over time.
How AEOVisor helps
The parts of the product that do the work described above.
Sentiment and framing, per engine
Sentiment is assessed against how your brand specifically is described, so a broadly positive answer that criticises you in particular doesn't read as a win.
Source-level visibility
See which domains assistants pull from when describing you — the direct input list for PR outreach and correction requests.
Evidence you can show a stakeholder
Every sentiment score links to the raw AI answer. When you tell an exec that an assistant is repeating something false, you can show them the text.
PR & brand teams: common questions
Practical answers, including where this is genuinely hard
Not directly — there's no submission form. What works is changing what the assistant retrieves: publish clear authoritative content, get accurate coverage on sources they already cite, and make sure your own site is crawlable and unambiguous. Some providers offer feedback mechanisms, but retrieval influence is the reliable lever.
Other teams using AEOVisor
SEO & AEO teams
You already own organic performance. Now leadership wants to know what happens when ChatGPT answers the question instead of Google — and whether the traffic you're losing is going somewhere you can influence.
Read moreContent teams
Being told you're invisible in AI search isn't useful on its own. What you need is the specific prompt you're losing, the competitor being cited instead, and the page that would fix it.
Read moreDeveloper teams
Most AI visibility problems are technical before they're editorial. If GPTBot can't fetch the page, nothing else you do matters — and a surprising number of sites block it without knowing.
Read more