Gemini · LLM monitoring
Monitoring Gemini is monitoring Google’s AI surfaces
You still optimize for blue links, but users already see AI-generated summaries blended with Search. Gemini powers Google’s AI experiences, including AI Overviews—tracking Gemini ties classic SEO signals to how Google’s AI retells your category.
What a finished report looks like
The sample highlights Gemini’s row in the model table and quotes sourced from Gemini answers in the demo run.
Carapelli
Mentions by model (demo run)
Highlight: Gemini — the focus of this landing page. Numbers are illustrative.
Competitors in this slice
Your real report uses the same layout: scores, per-model breakdown, quotes, competitors, and citations — with your brand and the models you select.
Benchmarking
Timestamped snapshot
Completion time is stored with every run—clean before/after comparisons when you change positioning or content.
Method
Organic-style prompts
Your brand name is not pasted into the question text; we score whether models still mention you in realistic category queries.
Context
Around Gemini
Add sibling models in the same check to see if the pattern is specific to Gemini or repeats across the stack.
About this model
Because Gemini is wired into Google Search, cues from the web index and freshness directly influence whether an AI overview mentions your brand or a competitor.
In Russian Google, AI Overviews roll out unevenly—your first recurring snapshot establishes a baseline before the surface changes again.
How we measure visibility
Organic prompts without the brand name in the question; we score mentions, lists, and sentiment in Gemini’s answers.
- One run: Gemini + ChatGPT + Claude + Perplexity, and more
- Competitors, quotes, LLM-Score, and share of voice
- Dated reports after site or knowledge updates
Inside the report
Snapshot header
Completion time and which models ran—your anchor for before/after benchmarking.
LLM-Score & share of voice
Aggregated 0–100 signal plus the share of models that mentioned your brand at least once.
Competitors & roundups
Who appears next to you in Gemini answers: names, frequency, comparison or recommendation context.
Quotes & wording
Answer excerpts for manual review—how the model talks about the category and your brand.
Same prompts on other models
Parallel runs (Claude, Gemini, Perplexity, …) to see if the pattern is Gemini-specific.
From check to PDF-ready snapshot
Brand & niche
You set brand context, site, category, language, and check type—this selects the prompt pack.
Model mix
Pick the LLM families to include; the same scenarios run in parallel across all of them.
Server run
The job executes on our side; you can close the tab and open the report from History when ready.
Report
LLM-Score, share of voice, competitors, quotes, citations—exportable and rerunnable on demand.
If Gemini and classic SERP narratives diverge, revisit structured data, freshness, and corroborating sources.