In the age of AI, can your company, brand and products be seen by the models?

SEO optimizes ranking on search result pages, where users click through to you. GEO optimizes the answer AI gives directly — users may never click a link and still make a decision based on that answer. The techniques overlap (structured data, authoritative sources, content quality) but the goals differ: SEO is measured by ranking, GEO by being mentioned and recommended by AI.

Yes, but it is not a rebuild. The structured data, authoritative sources and content quality you already invested in SEO carry straight over — that foundation is shared. GEO adds three things: writing content in the shape AI prefers to cite (clear definitions, verifiable numbers, comparisons and steps); placing trustworthy information on third-party sources beyond your own site (AI often cites sources that are not your website); and measuring "mentioned and recommended in AI answers" instead of rankings. Put simply: SEO opens the door, GEO is what makes AI willing to say your name.

The check report is visible immediately. Systematic improvement depends on industry competitiveness, content supply and knowledge-base quality; monthly reports show the trend without promising a timeline.

The free check is a snapshot: whether your brand is currently mentioned by mainstream engines and roughly where it stands — enough to judge whether there is a problem. The paid plan is continuous monitoring: fixed question sets sampled on a schedule, competitor comparison, negative-mention alerts, source tracing, plus the content production and website rework capabilities to act on what is found.

The platform can be configured for domestic models only; calling overseas models requires your explicit authorization and is logged. Knowledge base documents are vectorized locally and used only for retrieval and writing references within your own account. Tenants are strictly isolated — even agencies cannot see another agency's client data.

Every sample records how it was captured — official API, UI simulation, manual entry or a third-party source — and the report and analytics console disclose the source composition up front. Different capture methods are never merged into one trend line: averaging official API results with manual entries yields a curve that looks perfectly normal, corresponds to a measurement that does not exist, and will suddenly jump the day you switch capture methods. The same applies across markets: a market we do not cover is labeled "not covered" rather than filled in with data in another language.

Yes. The platform separates a domestic edition from a cross-border edition: the domestic edition monitors Chinese engines and distributes to Chinese platforms; the cross-border edition connects to OpenAI, Perplexity, Gemini, Claude and overseas content platforms. Overseas sampling runs through an overseas egress node, and the two markets are metered separately. Each sample records which egress it used — different egress regions return different regional search results, so the two sets of samples cannot be compared directly.