AI Visibility

AI Visibility is an audit tool that measures how ready a website is to be crawled, understood, verified, and cited by AI answer engines such as ChatGPT, Gemini, Claude, Perplexity, Grok, and Google AI Mode. The premise behind it is that buyers increasingly ask an assistant a question instead of scrolling a page of blue links, and if a brand's site isn't legible to those systems, it quietly gets left out of the answer the buyer actually reads. The tool exists to make that gap visible. You give it a URL, it studies your site the way an AI crawler would, and it reports back on where your pages are clear, where they're thin, and where the facts a model needs to recommend you are missing or hard to verify.

Getting a report is straightforward. You enter your website URL and the tool generates a free locked report, then you spend credits to unlock the full findings. The crawl goes wide across the homepage, product and pricing pages, case studies, docs, help center, blog, sitemap, robots file, and even PDFs and less obvious entry points, so the picture reflects your whole site rather than a single landing page. From there it scores your presence across twelve audit domains, and that's the point where the free preview ends and the paid detail begins. The idea is that you can see the shape of the diagnosis before deciding whether the full breakdown is worth unlocking.

The depth is in what those domains cover. A brand entity profile clarifies who you are, what you sell, where your product boundaries sit, and which aliases or lookalikes could confuse a model. A claim-level evidence ledger maps each important claim to a source, a verification status, a freshness risk, and a note on whether it's ready to be cited. An AI intent coverage matrix checks whether your site can actually answer the recommendation, comparison, alternative, tutorial, pricing, trust, and buying questions people put to assistants. On the technical side it audits crawlability across robots, sitemaps, canonical tags, status codes, JavaScript rendering, PDF text, and image alt text, then recommends structured data like Organization, Product, FAQ, and Article markup where the visible content supports it.

Trust and competitive context round out the report. A trust signal gap analysis reviews authorship, update dates, company proof, certifications, named customers, contact details, and correction paths, since those are the things a model leans on to decide whether a source is credible. A competitor and off-site evidence map compares where rivals have stronger public proof across media, reports, partners, communities, app stores, and third-party references, which helps explain why an assistant might be recommending them and not you. Taken together, the twelve domains are meant to read less like a score and more like a working diagnosis your team can act on.

What keeps it practical is the output. Findings don't stop at a number, they turn into a P0, P1, and P2 roadmap with owner-ready tasks and acceptance criteria, which separates the technical blockers your engineers should fix from the content and authority work that belongs to marketing. Agencies and independent consultants tend to like this because the report packages cleanly as a client deliverable, and prospects can see partial results before anyone pays. It's aimed at AI visibility and growth teams, SaaS companies, Shopify and other ecommerce stores, and B2B service firms that have real credibility offline but weak, hard-to-verify proof online.

The sample cases on the site give a sense of the fixes the report surfaces. A Shopify skincare brand used it to find thin product education pages, missing FAQ blocks, and weak source references, then rewrote category guides and added schema-backed buyer questions. An early-stage AI workflow SaaS clarified product boundaries, added comparison pages, and published integration-specific use cases so it could answer buying-intent queries directly. A regional B2B services firm with strong offline credibility prioritized case evidence, service-area pages, and author details so both buyers and AI systems could verify it faster.

On pricing, the free locked report lets you review the structure and top-level findings at no cost, and unlocking full reports runs on credits rather than a subscription. Credit packs start small and stay valid for a year, so occasional audits don't force a recurring bill. It's worth knowing that the tool is upfront that it can't guarantee AI citations, since no product controls how a model chooses to answer. What it aims to do instead is make your site easier for those systems to crawl, understand, verify, and quote, and hand your team a clear queue of the work that gets you there.