The 'Search Everywhere' Protocol: Optimizing Beyond the Browser

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.

The 'Search Everywhere' Protocol: Optimizing Beyond the Browser

Search used to mean a browser and ten blue links; today a buyer asks the same question inside ChatGPT, through Siri while driving, inside a Slack copilot, or via Alexa on a kitchen counter, and each surface pulls from a different mix of knowledge graphs, cached web data, and live retrieval. Optimizing only for classic SEO leaves a business invisible on every one of these newer surfaces, because voice and in-app assistants strip away visual ranking entirely and return a single spoken or written answer with no second-place finisher. Winning across this fragmented landscape requires the same underlying identity — structured data, an llms.txt briefing, a consistent knowledge-graph entity — expressed consistently everywhere a model might retrieve it from, so that whichever assistant a customer happens to be holding, the facts it surfaces about your business are accurate, current, and attributed correctly rather than stitched together from outdated directory listings.

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Questions

Answered.

Do voice assistants like Siri and Alexa pull from the same data as ChatGPT?+

No. Voice assistants lean heavily on structured local-business data, knowledge graphs, and licensed data partnerships, while chat-based assistants blend that with live web retrieval and model training data — which is why consistent structured markup across all sources matters more than optimizing for any single one.

Is it possible to optimize for every AI surface at once, or do they require separate strategies?+

The foundation is shared: accurate JSON-LD, a clear llms.txt file, and a consistent entity across the web feed every surface simultaneously. Surface-specific nuances exist, but a fragmented, inconsistent web presence is the main reason businesses disappear from newer channels.

Why do in-app copilots (like a Slack or CRM AI assistant) matter for a local business?+

Increasingly, B2B buyers research vendors through copilots embedded in the tools they already use rather than opening a search engine at all — if those copilots retrieve from the open web or licensed data partners and your entity is unclear there, you lose consideration before a browser is ever opened.

The decisive search now happens inside an app, a car, or a voice assistant — never a browser tab.

The 'Search Everywhere' Protocol: Optimizing Beyond the Browser

Answered.