FAQ finder & FAQ builder

What does your industry ask the AI?

15 typical concerns of your audience as questions – for each, the sentences on your site that relate to it. Then the check: answered, partly or not – only with a verbatim quote from your site. Finally FAQPage JSON-LD, an HTML block and Markdown for llms.txt.

Four steps, nothing invented

1 · Topic from your home page

Title, description or H1 – without the brand name. You see it before the run and can change it.

2 · 15 concerns as questions

A fixed grid (price, shipping, warranty, compatibility …), phrased for your topic. No search volumes, no statistics – a draft you review.

3 · Matching sentences on your site

Home page, service pages (shipping, returns, FAQ, terms …) and the most relevant pages from your sitemap (FAQ, guides, categories, brands). You see the sentence, the page and the word found – only whole words count. This is a pre-filter, not a verdict yet.

4 · Answers with source obligation

Every draft rests on verbatim quotes from your site that the server verifies; a second check makes sure every statement is covered by the quotes. Result per question: answered, partly or not answered. You review and edit every answer before export.

To be honest: A FAQ makes a question answerable – whether ChatGPT or Perplexity then cites your answer is something no one can guarantee. Whether anything changes is what the mention check shows over the weeks.