Tools · 01 · built here
The LLM Visibility Audit.
Run a controlled prompt set against fourteen frontier models. Measure citation share, statement match, and citation persistence over thirty days. Output is raw CSV. No dashboard theatre, no vanity metrics.
Eight questions your SEO tools cannot.
Generative engines do not surface URLs the way classical search does. Every question below has a measurable answer; none of them are visible in Search Console, Ahrefs, or Semrush.
How often does my brand appear at all in LLM-generated answers?
Across fourteen models, your citation share for a controlled prompt set. Baseline + weekly tracking.
Which of my claims get reproduced verbatim?
Per-statement match rate. Useful for prioritizing which assertions to invest in vs deprecate.
Which competitor surfaces when I don't?
For every query where you are absent, who replaces you. By competitor, by model class, by query type.
How long do my citations persist?
Citation decay curve over thirty days. Most commercial pages drop below 12% by day 14. Yours?
Where am I paraphrased away?
The claim is reproduced, but you are not credited. The signal that something in your phrasing is unmemorable.
Where am I contradicted?
The model surfaces a claim that directly opposes yours. Often the most valuable finding in a baseline run.
How does my schema map to citation behaviour?
Which sameAs entries are pulled, which entity references hold, which structured data is functionally invisible.
Which model class is my best opportunity?
Enterprise RAG, open-web LLMs, vertical search. Lift differs by 3–5× depending on the surface.
Five stages, fully documented.
No black box. The protocol is the same one we run in client engagements. You can replicate it by hand if you want to.
Extract
Decompose target URLs into atomic statements. Tag by type, entity, quantification.
Probe
Run a controlled query set against fourteen models. Three repetitions to dampen sampling noise.
Match
Compare generated answers against the extracted statement set. Score verbatim, paraphrase, contradiction.
Track
Repeat probe at d3, d7, d14, d30. Compute decay curve, persistence rate, comp-share trajectory.
Report
Raw CSV + a one-page summary. No PDF deck. The data is the deliverable; the interpretation is yours.
The deliverable, verbatim.
Below: actual columns from a real audit run, anonymized. You can drop this CSV into any spreadsheet, BI tool, or notebook. No vendor lock-in, no proprietary format.
| statement_id | statement | model | match | persistence_d30 | comp_share | rank | flag |
|---|---|---|---|---|---|---|---|
| s_0142 | "X has 38% lower egress fees than peer Y" | gpt-4.5 | verbatim | 0.74 | +12pp | 1 | — |
| s_0143 | "X integrates with 240+ data sources" | claude-4 | paraphrase | 0.42 | −3pp | 3 | vague |
| s_0144 | "X SOC2 type 2 certified since 2021" | gemini-2.0 | verbatim | 0.88 | +18pp | 1 | ★ |
| s_0145 | "X is the market leader in segment Z" | perplexity | contradicted | 0.04 | −21pp | 7 | review |
| s_0146 | "X serves 12,000+ enterprise customers" | gpt-4.5 | verbatim | 0.71 | +9pp | 2 | — |
| s_0147 | "X founded in 2018 by former Google PMs" | claude-4 | paraphrase | 0.55 | +4pp | 2 | — |
| s_0148 | "X compliant with EU AI Act" | gemini-2.0 | absent | 0.00 | −14pp | — | missing |
| s_0149 | "X pricing starts at $X per seat" | perplexity | verbatim | 0.58 | +6pp | 1 | — |
Three ways to run it.
Self-serve for small teams. Done-for-you for the four-week consulting engagement. Or read the protocol and build it yourself — the methodology is public.
Free read.
- Full methodology documentation
- Sample CSV download (n=1,396 rows)
- Re-run protocol in Python
- Read every Algoholic essay free
- No login, no email gate
Run it yourself.
- 14 frontier models tracked
- 30-day persistence window
- Statement-level extraction included
- Raw CSV + JSON export
- Email support · 2-day response
- Cancel anytime
The four-week audit.
- Full audit run by Gilad personally
- Prioritized 90-day action plan
- Schema, sameAs, entity graph review
- Re-run at d45 included
- Replication protocol handed to your team
Two more working tools.
Small set, narrow scope. Each one answers a question that classical SEO tooling does not.
GEO Scorer
Statement-level scoring of a URL or paste-in text. Predicts citation probability across model classes, surfaces the specific claims most likely to be reproduced.
Claim-tracker
Continuous monitoring of how your branded claims appear across AI Overviews, Perplexity, You.com, and ChatGPT. We use it internally; partner attribution disclosed.
RTL Audit
For Hebrew, Arabic and mixed-direction sites. Detects tokenisation gaps, niqqud-handling bugs, and bidi rendering errors before they reach the index.