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AI business presence
Measures how selected third-party AI assistants describe and recommend a business.
EVIDENCE BEFORE CLAIMS
See exactly what was measured before deciding what to change.
Verify Presence measures how selected AI assistants describe and recommend a business. It preserves the exact questions, answers and returned sources, separates mentions from recommendations and factual accuracy, and prepares evidence-backed improvements for approval and comparable remeasurement.
The category boundary
AI business-presence measurement, clearly separated from adjacent tools.
Clear boundaries matter because “AI presence” is often confused with receptionists, local-marketing automation and software observability.
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Not AI reception
Does not answer calls, qualify leads, schedule work or run customer messaging.
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Not internal observability
Does not monitor an AI application or model that the customer operates.
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Not rank tracking
Does not turn variable AI answers into a universal or guaranteed ranking.
Worked method
A transparent example from question to remeasurement.
This is a synthetic method example, not a customer result. It illustrates the evidence chain without claiming a ranking, recommendation or improvement.
Freeze a buyer-shaped question
Example: “Which UK services can help a specialist contractor understand how AI assistants describe its business?” The business is not named or hinted at.
Preserve the observed answer
Record the exact question, selected system and model context, measurement time, full answer and returned public sources.
Review separate signals
Record mention and recommendation separately. Check material statements against approved evidence and leave unsupported points unresolved.
Prepare one bounded improvement
If an important fact is absent or wrong, draft an evidence-backed correction for a named page or public source. A person approves any public change.
Remeasure comparably
After the approved change is public and an observation window has passed, repeat the same question and context. Show what changed, what did not and what remains uncertain.
What the service measures
Separate observations instead of one misleading score.
Every result stays tied to its frozen questions, selected systems, model context, date and evidence review.
Mention share: the percentage of measured answers that name the businessRecommendation share: the percentage that actively present it as a provider to considerCorrect, partial, incorrect and unresolved statementsReturned citation and source coverageCategory or proposition misunderstandingChanged, unchanged and unresolved remeasurement results
SYNTHETIC METHOD EXAMPLE · NOT A CUSTOMER OUTCOME
3separate observations
Mention: the business appeared in an answer.
Recommendation: the answer actively suggested the business.
Accuracy: the material statement was supported, contradicted or unresolved against approved evidence.
Start with the baseline