12
3
5
42%
5 of 12 addressed
Each gap type requires a different fix. Surfaced identifies them separately so you always know what action to take.
AI stated something that contradicts your knowledge base — wrong facts, incorrect product details, or outdated specs.
AI could have said more from your knowledge base but didn't — your best features go unmentioned when users ask.
AI is referencing old facts when your knowledge base has the updated version — pricing, features, or company info.
AI praised a competitor for something your brand also offers — or better. You're getting overlooked in your own category.
A topic has no knowledge base content to support a good AI response — AI defaults to competitors because you have nothing to cite.
Consistently negative AI sentiment on a specific topic — the model has absorbed a negative impression that your content needs to correct.
Surfaced queries ChatGPT, Claude, Perplexity, Gemini, and DeepSeek with your tracked prompts. Every response is stored and indexed.
Responses are weighted by recency, sentiment polarity, and prompt intent (comparison queries score highest — they have the most business impact).
Each response is compared against your knowledge base using semantic search. Divergences — missing facts, wrong claims, outdated data — are flagged as gaps.
Gaps are grouped into thematic clusters using AI semantic analysis. 'Pricing unclear' and 'costs not shown' become a single actionable theme.
Each cluster produces prioritized content suggestions: new articles, KB updates, FAQ entries, or talking points — with outlines ready to generate.