SearchScore Intelligence: an explainable engine that measures whether its advice worked
The platform pairs the Knowledge OS with a recommendation engine that scores its own confidence, refuses to guess, and is built so it cannot publish a result it has not measured.
SearchScore today launched SearchScore Intelligence, bringing its knowledge, reasoning and measurement together into one platform.
At its centre is an engine you can ask in plain English: describe a visibility problem and get a diagnosis, the relevant framework, and a prioritised action — each with a real, measured confidence score. When the engine is not sure, it refuses rather than guesses. A false refusal beats a confident wrong answer.
Its defining principle is a measurement discipline built into the core. SearchScore records whether its recommendations move a real site's visibility, weights that evidence by quality and recency, and will report a success rate only once it clears a strict evidence bar — with the sample size shown. The system is engineered so an unproven number cannot surface at all. In a market full of confident, unprovable claims, that restraint is the product.
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About SearchScore. SearchScore is a London-based AI search visibility platform and consultancy. It measures how easily AI answer engines and search engines find, trust and cite a website across AI search visibility (GEO), SEO and conversion (CRO), grounded in a benchmark of more than 850,000 audited sites. Its methodology is authored by founder Ronnie Huss.