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AVE Studio · AI Visibility Engineering

Research — how machines see businesses

Field research on how machines see businesses — measured, dated, and honest about its limits. Small samples, real probes, no inflated numbers.

What this is

AVE Studio publishes repeated measurements of what AI answer engines cite and recommend when people ask a category's real buying questions. Each release is a dated run against a fixed, versioned panel — not a one-off query, and not a leaderboard. What we publish is what we observed, with the sample it came from.

The instrument, honestly

Engines measured
Claude, ChatGPT and Gemini, plus Google AI Overviews — the AI surface of Google Search, reported as a Google surface rather than as a fourth independent model.
Versioned panels
The prompt panel for a release is fixed and version-stamped before the run. A panel change starts a new version rather than editing a published one, so two releases are comparable or explicitly are not.
Dated runs
Every figure carries the date it was measured. AI answers move; a number without a date is not a measurement.
Observation language
We report what was observed, with its sampling range. We do not report a single combined score, and we do not claim that any change we made caused any change we measured.

Releases

Measurement reports

Which is the best AI visibility agency?

The terms these releases use

Field studies

Measurement notes

  • Which AI searches, and which answers from memory?

    Same question, same day, three engines — and three entirely different machines. 180 measured runs, from an AVE Studio field note.

    measured · k=5 · openai, gemini, perplexity