Is AI visibility the same as SEO?

No. AI visibility is whether AI assistants name your tool when a buyer asks for a recommendation; SEO is your rank in the blue links. The two overlap only partly, so AI visibility is a separate, winnable race.

How is the AI-Visibility Score calculated?

It is a position-weighted count of how often a tool is recommended across the query set (a #1 recommendation counts more than a #5), normalized 0 to 100 and rewarded for breadth across categories. The full method and open data are on this page.

Does this rank product quality?

No. It measures what AI engines OUTPUT when asked, not which tool is objectively best. AI outputs reflect what their training data or the live web says, and can be wrong or biased. Treat it as a visibility snapshot, not an endorsement.

Why do the engines disagree so much?

Model-memory engines recall the established names from training data, while web-grounded engines read current pages and surface newer or trending tools. Same question, different information source, different answer.

How often is it updated?

It is a dated snapshot. AI answers shift, so the protocol is built to be re-run, and each refresh produces a delta showing how the recommendations moved.

LucreyaResearch › The AI Recommendation Audit 2026

Measurement independence

This ranking is unpurchasable

The commitment below is the reason the number is worth reading. It was written in July 2026, before any vendor was contacted, and it governs every page in this audit.

This ranking is unpurchasable

No vendor can pay to change its position, score, or inclusion in this measurement. We measure what AI assistants actually recommend, and nothing here is sponsored, and a vendor's score is never influenced by any commercial relationship with us.

DeepSynthesis does run clearly-labeled sponsored placements on some of its category sites. Those are a separate, disclosed surface and do not touch this measurement: we never sell measurement and placement to the same vendor in the same category, and no sponsor sees this data before it publishes. That separation is the whole point: it is why the number is worth trusting.

Method: N independent runs per query, disclosed variance and confidence intervals, deterministic vendor extraction from the raw answer text, DOI-versioned.

What that means in practice

Separable and unpurchasable. The measurement is a distinct instrument. No vendor's score can be bought, moved, or influenced by a placement relationship.
No pre-publication access. No sponsor sees or touches measurement data before it publishes.
Separate surfaces. The measurement lives here. Sponsored placement lives on the category sites, clearly labelled. A page that measures does not sell.
A conflict does not buy an exemption. Where a vendor already holds a paid placement in a category we measure, they are still measured neutrally , and excluded from measurement-related outreach.

Read the audit, or the open dataset it is computed from.