AI search analyticsfor marketing teams

Whether AI assistants recommend you, not whether they mention you. Every recorded answer is judged on a five-level endorsement scale — from named as the choice, down to named and advised against — and that judgment multiplies the score before position or prominence are considered. A brand named first in an answer that then argues against it scores zero, the same as one that was never named.

A mentions report counts appearances. Vidrys scores the quality of the appearance, samples each prompt more than once so the number rests on a distribution, version-stamps every score so a formula change cannot rewrite your history, and carries each finding through to a drafted fix and a re-measurement. The difference shows up when a mention count rises and the shortlist has not changed.

That variability is the reason single-screenshot tools mislead. Every prompt is re-probed on each sweep — and drawn more than once within a sweep on Grow and above — with scores, win rates and trends computed across those draws: “recommended in 8 of 12 answers” rather than one answer treated as a fact. Each score also carries a confidence interval, and a week-over-week move that does not clear it is reported as inconclusive rather than as a change.

The record attached to a single answer: which competitor was recommended, which sources the model actually leaned on, and the specific claim your pages failed to support. It is what the drafted fix is written against. When the evidence in an answer is too thin to support a reason, the card says so instead of inventing one.

ChatGPT, Perplexity, Gemini, Copilot, Google AI Overviews and Claude. How many run on each sweep depends on your plan — two on Track, three on Grow and Scale — because every additional engine multiplies the number of answers analyzed, and an all-engines default would quietly multiply what you are billed for. Track can add Google AI Overviews; Scale and Custom can add Gemini, Claude and Copilot. The per-plan sets are listed in full on the pricing page.

The score has a trust factor — how authoritative the citing sources are — that is specified but not yet built. Rather than approximate it, the remaining weights are renormalised and the omission is stated in the product. We also do not measure private or logged-in assistant sessions, and we do not claim a causal link between a published fix and a score move: the product reports the baseline window, the current window, and whether the difference clears the confidence interval.

SEO optimises for a ranked list of links. The inputs that decide an AI recommendation are different: whether a crawler can read the page at all, whether a claim is stated somewhere a model can cite, entity clarity, and which third-party sources the model already trusts. Vidrys audits the first, detects the second, and reports the third from the citations in your own answers.

Yes, once you approve them. Drafts are written against your own crawled pages so they read like your site rather than generic filler, and they publish to WordPress, Webflow, Shopify or Ghost. Nothing is published without approval.

We do not publish a timeline, because we do not have the cohort to support one and the honest answer depends on your cadence, your engines and what you ship. What the product does commit to is telling you when a move is real: each sweep re-probes the same prompts through the same scoring pipeline, and a difference that falls inside the confidence interval is reported as inconclusive rather than as progress.

Sign up, add your brand, your competitors and the prompts you want tracked. No card is required to start, and each new workspace is reviewed before we activate it. If you would rather see it against your own brand first, book a demo.