Website readiness
84 / 100
Public pages were reachable and the key offer was parseable in this illustration.
Public example · reviewed
AI Discovery sample report
See how Prompeteer separates website readiness, answer evidence, citations, recommendation position, sentiment and action planning in one dated report.
Illustrative report. Values and model names below are a fictional example created for product education. They are not a customer measurement and do not refresh.
Readiness snapshot
A report starts with the evidence available on the collection date. A missing measure is labeled explicitly rather than converted into a zero.
Brand mentions
8 / 24
Eight of twenty-four completed answers named the sample business.
Citations
14 / 24
Fourteen completed answers included at least one recorded source.
Recommendation position
Top three in 5 / 8
Five of eight eligible answers placed the sample business in the first three recommendations.
Brand sentiment
62% positive
Eight named answers were assessed: five positive, two neutral and one mixed.
AEM actions
4 proposed
Four evidence-linked actions are ready for owner review; proposal is not implementation proof.
Evidence coverage by section
Completion, mention, citation, sentiment and planning evidence answer different questions. Keeping them in separate rows prevents a complete API response from being mistaken for a complete business assessment.
| Report section | Coverage | Recorded evidence |
|---|---|---|
| Website readiness | Observed | 84 / 100 Seven checks passed, one needs review and two were not applicable. |
| Answer collection | Measured | 24 / 24 complete Three web-grounded engines and five model-memory proxies completed the same six questions. |
| Brand mentions | Measured | 8 / 24 named A mention rate is calculated from completed answers and is separate from citation rate. |
| Citation evidence | Measured | 14 / 24 answers cited Recorded citations include source URLs and exact destination pages when available. |
| Recommendation position | Measured | 5 / 8 top-three Position is reported only for answers that contain an explicit ordered recommendation. |
| Brand sentiment | Measured | 8 assessed mentions The classifier labels the answer wording and stores a quote for every assessed mention. |
| Forecast outlook | Not yet measured | History required A forecast is withheld until comparable dated reports have enough history for validation. |
Model and layer results
The same six buyer questions run across each configured engine. The layer identifies whether the answer used web retrieval or model memory; a zero named rate is a measured result, not a failed call.
| Model | Layer | Completion | Named | Citations |
|---|---|---|---|---|
| OpenAI API | Web-grounded | 5 / 6 complete | 2 named | 3 citations |
| Perplexity API | Web-grounded | 6 / 6 complete | 3 named | 5 citations |
| Gemini API | Web-grounded | 6 / 6 complete | 2 named | 4 citations |
| Meta API | Web-grounded | 6 / 6 complete | 1 named | 2 citations |
| Grok API | Web-grounded | 6 / 6 complete | 2 named | 3 citations |
| DeepSeek API | Model memory | 6 / 6 complete | 0 named | — |
| Qwen API | Model memory | 6 / 6 complete | 0 named | — |
| GLM API | Model memory | 5 / 6 complete | 0 named | — |
Method and next step
Prompeteer asks stable, buyer-relevant questions, records raw answers and citations, extracts explicit recommendations and stores exact quotes for sentiment review. Comparisons use compatible dates and question sets. The private report adds the answer matrix, competitor context selected by the account owner, prior versions and an AEM work queue.
Read how to interpret AI visibility measurements · See the AEM action-plan workflow · Choose a plan