Use case

Monitor what AI says about you over time

Models change, competitors publish, and an answer that named you in March can quietly drop you by June.

The problem
What is actually happening

We fixed it once. Is it still true this month

AI visibility is not a project with an end date. The systems that decide who gets recommended are retrained, re-ranked, and re-grounded continuously. A one-off fix tells you nothing about whether the position held, and by the time someone notices anecdotally, the drift is months old.

How we fix it
The work

What the engagement involves

  • Track a fixed question set across the assistants your buyers use.
  • Watch both the citation and the framing, since being mentioned dismissively is not the same as being recommended.
  • Flag movement against competitors, so a drop is caught as it happens rather than at the next review.
  • Feed what moved back into the content and authority work.
OUTCOME A continuous read on your position instead of a snapshot, and early warning when it starts to slip.
AI Visibility Index

Find out where you stand

When a buyer asks an assistant who to work with, it names two or three companies and moves on. The audit puts the questions your buyers actually ask to all five AI platforms, scores you on the five things a model weighs before it cites anyone, and shows you which competitor is named in your place. You get the gap and the order to close it in, five business days from briefing.