Comparisons
How AEOVisor compares to other AI visibility tools
Straight comparisons with real pricing, sourced claims, and an honest section on every page explaining when the alternative is the better choice. We'd rather you pick the right tool than the wrong one twice.
Pick a comparison
Each page covers pricing, engine coverage, measurement depth, the optimisation workflow, and who each tool genuinely suits best.
AEOVisor vs Ansvisor
Ansvisor is an open-source AI visibility platform with a paid managed cloud. AEOVisor is a managed product priced for teams that don't want to run infrastructure.
Read the comparisonAEOVisor vs Profound
Profound targets enterprise AI visibility monitoring at enterprise prices. AEOVisor does the same core job for teams without an enterprise budget.
Read the comparisonAEOVisor vs Otterly.ai
Otterly.ai is the closest competitor on price. AEOVisor adds Search Console data, SERP tracking, technical auditing and free tools at a comparable cost.
Read the comparisonAEOVisor vs Semrush AI Toolkit
Semrush's AI Toolkit extends a mature SEO suite into AI visibility. AEOVisor is built for answer engines from the ground up.
Read the comparisonAEOVisor vs HubSpot AEO Grader
HubSpot's AEO Grader is a free one-off score. AEOVisor is continuous monitoring with the fixes attached.
Read the comparisonHow we write these comparisons
Vendor comparison pages have a deserved reputation for being dishonest. These are the rules we hold ourselves to — you should hold every vendor to them, including us.
Every claim is sourced and dated
Each page lists the sources we checked and when we checked them. Pricing in this category moves constantly, so a stale claim becomes a false one. If something is out of date, tell us and we'll fix it.
We say when a competitor is better
Every page has a section explaining who should choose the alternative, naming the features they have that we don't. A comparison that wins every row isn't a comparison — it's an advert.
We don't guess
Where we couldn't verify a capability from public sources, it's marked unverified rather than marked absent. Absence of evidence isn't evidence of absence.
No invented proof
No fabricated testimonials, no borrowed logos, no metrics we can't stand behind. If a number appears on these pages, we can show you where it came from.
What to look for in any AI visibility tool
Useful whether or not you end up choosing us. These are the questions that separate a real measurement product from a dashboard.
How many AI engines does my plan actually include?
Not how many the product supports — how many are included at the tier you'd buy. Coverage is often gated hard at entry level, and a score from two engines can't tell you much about a market where buyers use six.
Is the scoring methodology published?
If a vendor won't tell you how the number is calculated, you can't sanity-check it, defend it internally, or tell a real change from a methodology change. Ask for the formula and the component weights.
Can I see the raw AI answer behind a score?
The single best test of a visibility product. If you can't click from a number to the actual sentence in the actual answer that produced it, you're being asked to trust an index.
Does the vendor control its own measurement?
Some platforms depend on an outside data supplier for the core signal. That's a single point of failure you can't fix and can't see — worth asking about, because their outage becomes your blind spot.
Does it tell me what to do next?
Measurement without a fix list is a report, not a tool. Look for whether it connects visibility gaps to specific pages, schema issues, crawler access problems and content opportunities.
Can I export and leave?
Check before you commit, not after. Data portability is the difference between choosing a vendor and being stuck with one.
Choosing between AI visibility tools
Questions worth asking every vendor on your shortlist
Run the same set of prompts through each tool and compare the evidence, not the headline scores — different vendors weight things differently, so the numbers aren't comparable across products. Then ask three questions: how is the score calculated, can I trace a number back to a specific AI answer, and can I export my data. Opacity and lock-in are the two things that hurt later.