Prism Optimizer grades and optimizes your website content for both — the AI engines now answering your buyers’ questions (ChatGPT, Gemini, Perplexity, Claude, AI Overviews) and the search rankings that still send the traffic. Ten dimensions, one Prism Score, and the fix simulated before you publish it.
AI engines don't rank pages — they select sources. The Prism Score grades every page on your site across the ten dimensions that decide whether an engine selects you: from core intent and implied questions to whether an engine can retrieve, extract, cite and reuse what you wrote.
Dimension names are the live scoring rubric. Grades shown are illustrative sample data.
Every scan pulls current data from the surfaces where answers actually happen — so you're optimizing against today's results, not last quarter's export.
Which of your keywords trigger an AI Overview, who's quoted inside it, and whether that's you or a competitor.
Question-level ownership: the PAA boxes your pages hold today, and the open questions you could claim next.
Where every page actually sits today — pulled fresh each scan, never carried over from a stale export.
AI engines fan one question out into many. Prism fetches the query variants live and maps the ones your pages must answer to stay in the result.
The long-tail phrasings and unusual intents where answers swing — fetched live, so wins there aren't left to chance.
Keyword-level volume behind every recommendation — never inflated grouped totals.
Every card above is a live fetch, run per scan and scored into the Prism Score. Competitor scores and publishing velocity are fetched live too — see section 05.
Each engine selects sources differently. Prism builds prompt sets from your pages' real intents, runs them live across ChatGPT, Gemini, Perplexity and Claude, and records the outcome — cited, mentioned, or absent.
No other step in your content process lets you see the result before you ship. Prism's Optimize workbench does: it drafts the rewrite in your brand voice, then simulates the new Prism Score — before a word goes live.
Illustrative example of the rewrite → simulate flow. Simulated scores use the same deterministic engine as live scans.
Visibility is a race for the citation. Prism tracks your competitors' publishing velocity — how many pages they ship per month, what they published this week, and how their Prism Scores compare to yours, run over run.
Re-scan on your cadence with a "what changed" report after every run — real movement separated from measurement noise.
Every scan is kept, so the Prism Score is tracked over time per page — you can show movement, not just a snapshot.
Verified, modeled or benchmark — each figure is labeled with its source. No silent estimates, in the app or the boardroom.
Every scan produces one comprehensive audit — page by page, dimension by dimension, with the live evidence behind each number and the fixes ranked by what actually moves the Prism Score.
The blog home — sourced, practical writing on AI visibility. Cards below are samples.
Structural patterns shared by pages AI engines cite — and the ones they pass over.
How a composite, deterministic score keeps optimization honest — and comparable over time.
What competitor output actually predicts about citation share, from live tracking data.
A live walkthrough on your own site — your pages, your citations, your gaps across every AI surface.
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