Scan module · Use case
Audit AI visibility before a product launch
You are about to launch, and no AI engine has any idea the new product exists or which category it belongs to. A pre-launch baseline shows exactly what the engines currently believe, so launch content can target the gaps instead of guessing.
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How do you audit AI visibility before a product launch?
A pre-launch baseline shows exactly what the engines currently believe, so launch content can target the gaps instead of guessing. The work runs in four steps: baseline category prompts before any launch content goes live; identify which competitors currently own the answer; publish launch material that makes your category membership unambiguous; re-run weekly through launch to watch the engines pick it up. A launch that registers with AI engines in weeks rather than the following year.
Key facts
- Job to be done
- Audit AI visibility before a product launch
- Platform module
- Scan
- Typical owner
- Product marketing leads
- Available from
- Starter — $59 / month
- Engines covered
- ChatGPT, Gemini and Claude
- Outcome
- A launch that registers with AI engines in weeks rather than the following year.
The problem
You are about to launch, and no AI engine has any idea the new product exists or which category it belongs to.
This is not a reporting inconvenience — it is a measurement gap. AI answers are generated fresh each time and vary between sessions, so anecdotal checks cannot establish a trend and cannot prove whether anything you changed made a difference.
How Geosystems AI handles it
A pre-launch baseline shows exactly what the engines currently believe, so launch content can target the gaps instead of guessing.
- Baseline category prompts before any launch content goes live.
- Identify which competitors currently own the answer.
- Publish launch material that makes your category membership unambiguous.
- Re-run weekly through launch to watch the engines pick it up.
What you get
Everything below lands in your private workspace and is exportable as PDF or CSV, so the evidence travels with the decision.
| Output | What it contains |
|---|---|
| Pre-launch baseline | What every engine says before you start |
| Category ownership map | Who currently gets named for your category |
| Gap list | The facts no engine can currently verify about you |
| Weekly launch tracking | Adoption curve across ChatGPT, Gemini and Claude |
What good looks like
A launch that registers with AI engines in weeks rather than the following year.
The measurement backbone is the same across every use case: GVI™ scores each answer on Presence, Prominence, Attribution, and Accuracy, while Recommendation Share™ places that score against the competitors you name. Both are re-run on a schedule so movement is a trend, not a screenshot.
Audit AI visibility before a product launch
Free checks send three identical prompts to ChatGPT, Gemini and Claude live. Failed engines are unavailable and excluded from measurements.
Frequently asked questions
Who typically owns this inside a company?
Product marketing leads. In smaller teams it usually sits with whoever owns demand generation, because the impact lands on pipeline first.
Which plan do I need?
Starter — $59 / month. Starter is $59 per month, Growth is $119 per month, and Scale is $199 per month. Annual billing is discounted.
Does this cover every AI engine?
Yes — ChatGPT, Gemini and Claude are all tracked on the same prompt set, so results are directly comparable between engines.
How do I try it before subscribing?
Free checks send three identical prompts to ChatGPT, Gemini and Claude live. Failed engines are unavailable and excluded from measurements.