Enter any topic or prompt. See the 8–16 sub-queries an AI search engine would fan it out into — grouped by intent, visualized as a live branching tree.
Free · runs in your browser · nothing sent to any server
These sub-queries are machine-generated — they live inside the AI engine's retrieval layer, not in any keyword tool. Your pages get cited through queries nobody ever types. That's the point of covering the cluster.
12 sub-queries across 6 intent categories
Want a real model's decomposition instead of a heuristic preview?
Copy this and paste it into ChatGPT, Claude, or Gemini to get a real model's fan-out decomposition of your query.
When someone asks an AI engine a question, the engine doesn't run that question as a search. It fans out into 8–16 parallel sub-queries, retrieves the best source for each, and synthesizes one answer with citations. Your page gets cited if it matches one of those sub-queries — not the prompt the human typed.
This breaks classic SEO intuition. The queries that actually retrieve your page have zero measurable search volume in any keyword tool — they're machine-generated on the fly. The implication: stop targeting one keyword. Map the full cluster of sub-questions an engine would generate, give each its own answer-first section, and you become eligible for citations across the whole fan-out.
This tool gives you a structural preview of that fan-out. It's heuristic — it applies known templates to your input — not a live model call. For a live model's actual decomposition, use the copyable simulator prompt above. For the full depth on the mechanic: read the companion deep-dive →
The fan-out preview shows you which sub-questions to cover. LumenGEO shows you whether ChatGPT and Perplexity are actually citing you right now — with live AI queries and competitor tracking.