Aetos SEO is a WordPress audit plugin for site owners and developers who want to review SEO and AI visibility issues in one place. It scans more than 200 technical, content, schema, link, and AI-readiness signals, then shows what is wrong, where it happens, why it matters, and what to fix next.
Inside the plugin, users can run audits, see scores, and watch progress live from a dashboard. Individual finding details include evidence, affected pages, fix steps, and a verification method. Settings include scan depth, scan type, email summaries, and English or Arabic admin mode. The product also includes AI-readiness scoring across AEO, AIO, and GEO, along with an export that packages audit context as JSON for ChatGPT, Claude, or a developer. The exported file includes the page, the element, why it matters, and the context needed to draft a fix plan.
Aetos is delivered as a WordPress plugin, and the site also offers a free audit for any public URL without a WordPress install or signup. The free audit is separate from the plugin, which adds the deeper in-WordPress audit and AI-ready JSON export. The pricing shown is $79 per year at launch. The product is described as built for Arabic and English, with support for hreflang, RTL detection, Arabic schema, and bilingual sitemaps. It is also described as a diagnostic layer rather than a writing tool: it does not generate content, meta tags, schema, or sitemaps, and it is meant to work alongside SEO authoring plugins rather than replace them.
In the SEO audit & analysis space, Aetos SEO takes a focused approach. It focuses on identifying and prioritizing technical SEO and AI-readiness issues on WordPress sites without altering existing SEO plugin settings. It is built as a consumer product for wordPress site owners and webmasters. It is available for free. It runs on the web.
It is developed by Aetos SEO, and it first shipped in 2026. Key capabilities include Technical SEO audit, AI-readiness check, and prioritized issue list. The interface is available in Tibetan and English.
Summary written by a language model from the project’s public pages.
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