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AI HALO

Learn · The mechanics of AI visibility

AI models don't match keywords to your business — they match your business to a knowledge-graph entity.

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Proof & data

Most AI-visibility tools only watch — they report where you are absent and stop there. AI HALO does the work that changes the answer, then re-scans to prove it.

$29–$780/mo
what monitoring tools charge to report your AI visibility
$1,500–$50k/mo
what GEO agencies charge to execute — ongoing retainer
One investment
what AI HALO asks to do the work + a 30-day proof re-scan

Measured live across ChatGPT · Claude · Gemini · Meta AI · Grok · DeepSeek — we ask the models your buyers’ real questions, before and after.

Entity SEO: How AI Models Actually 'Think' About Your Business

Large language models reason over entities: a business is represented internally as a node with attributes — category, location, ownership, relationships to other entities — rather than as a bag of ranked keywords. If that node doesn't exist cleanly, or if it's fragmented across inconsistent name variants, outdated addresses, and conflicting directory listings, the model either omits the business or, worse, confidently states wrong facts pulled from whichever source it could resolve. Entity SEO is the discipline of consolidating those signals: canonical Organization schema, consistent NAP data across every citation source, sameAs links tying the business to its verified profiles, and a defined relationship graph to its category and competitors. AI HALO builds this entity layer directly, then re-probes ChatGPT, Claude, and Gemini after thirty days to confirm the model now resolves the business to one accurate, well-formed node instead of an ambiguous or fabricated one.

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Questions

Answered.

What's the practical difference between keyword SEO and entity SEO?+

Keyword SEO optimizes for matching search terms; entity SEO optimizes for being correctly identified as a distinct, well-defined thing in a knowledge graph, which is what determines whether an AI model describes you accurately at all.

How does inconsistent business data cause AI hallucination?+

When a model can't resolve one canonical entity from conflicting name, address, or category data across sources, it fills gaps with statistically plausible but unverified guesses — producing wrong hours, wrong services, or a merged identity with an unrelated business.

Does having a Google Business Profile create an AI-readable entity?+

It helps but isn't sufficient alone. AI models draw on a wider set of structured signals — schema markup, Wikidata/sameAs links, and citation consistency — that a Business Profile doesn't fully cover on its own.

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