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.
Measured live across ChatGPT · Claude · Gemini · Meta AI · Grok · DeepSeek — we ask the models your buyers’ real questions, before and after.
A growing share of high-intent buyers now ask an assistant for a recommendation and act on the name it gives. When that name is a competitor, the loss never appears in your analytics — there is no click to miss, no bounce to diagnose. It is demand that reached the point of decision and quietly went elsewhere. Board-level teams under-react because the leak is invisible; the assistant simply never mentioned you. Quantifying it is straightforward: take your category’s buyer prompts, ask the leading models, and count how often you are named versus the competitors who are. The delta, multiplied by deal value, is your annual exposure. Most firms are stunned by the figure. Closing it is not a monitoring subscription — it is the work of becoming the recommended answer. That is what you invest in with AI HALO, and we prove the movement in 30 days.
Invest in your AI Halo →Questions
Monitoring tools measure the leak — they show you where you are absent, then stop. Useful, but a diagnosis is not a cure. AI HALO does the execution: we change the signals so the answer changes, then re-measure to confirm the recommendation now includes you.
Yes. Share-of-voice across your buyer prompts × your average deal value × your category’s query volume gives a defensible annual estimate. It is the same logic as unmeasured demand in any channel — made concrete by testing the models directly.
The signals compound. Competitors who structure their entity now accrue citation authority that is expensive to displace later. Waiting a cycle does not hold the position steady — it cedes ground while the model’s picture of your category hardens around whoever showed up first.