GEO Jetpack analyses AI Search from three angles at once — the prompts that surface your brand, the content that earns citations, and the knowledge graph that grounds both. Each pillar is deep enough to work as a standalone tool. Together, they explain not just what’s happening in AI Search, but why.
Explore the pillars ↓Traditional GEO tools measure one of these — usually visibility. GEO Jetpack measures all three, on every prompt, in one system.
How AI search engines respond to prompts about your brand — visibility, citation, sentiment, and position across every engine.
Which of your pages earn AI citations, which don’t, and why. Deep structural analysis of schema, entities, depth, and freshness.
Where your brand sits in the knowledge structure LLMs actually use — Wikipedia, Wikidata, Google KG, and industry sources.
Visibility measurement alone tells you a brand appears — not why LLMs mention it, or what content earned the mention. Content analysis alone tells you which pages are structurally strong — not whether they’re actually being cited. Knowledge graph analysis alone tells you where the brand sits in third-party sources — not how that translates to AI Search performance.
The three pillars are complementary because they cover the three separate systems that determine AI Search outcomes: the LLM response layer, the brand’s own content layer, and the third-party grounding layer.
When something moves in one, GEO Jetpack cross-references the other two to explain why. That’s the mechanism behind the ENQ™ recommendations — every action is grounded in evidence from all three pillars, not one.