See How AI Models Embed and Interpret Your Content

Yes. After parsing your content into logical sections, the tool scores each section using embeddings. You get a distribution chart showing which parts are Excellent, Strong, Moderate, or Weak. This makes it easy to prioritise which sections need rewriting or expansion.

Semantic scoring measures whether your content matches the intent behind a query, not just the words used. This makes it more accurate for LLM SEO and modern search, where AI tools evaluate meaning, relevance, and entities. Traditional keyword tools only check overlap, which often misses deeper context and nuance.

Yes. The recommendations highlight missing entities, weak topic coverage, or sections that do not fully answer user intent. You can see exactly which details AI systems expect and where your content falls short. This helps you create more complete and AI-friendly content.

Yes. You can input up to three LLM-style queries and up to ten Google Search Console keywords. The analyzer compares your content against both sets of inputs at the same time, giving you a clear sense of how well your content performs across AI and traditional search.

Improvements can include better alignment with user intent, stronger entity representation, clearer structure, and higher semantic scores. This can lead to increased visibility in Google Search and better chances of being cited or recognised by AI platforms like ChatGPT and Perplexity. The tool also lets you re-run analyses to measure progress over time.