Inspect the page as chunks
Rendered content is split the way a retrieval system would read it. You can see whether the opening states the topic, and whether later sections still belong to it.
Chunks, similarity, and the source URL stay attached to every match — so you can see what a model would retrieve, and from where.
Read the page in the chunks a model would use, run a query against the crawl, then see why a passage rose — or why a better one sat too far down.
Rendered content is split the way a retrieval system would read it. You can see whether the opening states the topic, and whether later sections still belong to it.
A natural-language query ranks passages by semantic similarity, not keyword overlap. Open any result to the matching excerpt and the URL it came from.
Weak retrieval usually has a structural cause: a buried answer, a heading that cannot stand alone, or an opening that does not match the rest of the page. The finding stays on that passage.
See the sections an AI system can retrieve on their own.
Catch openings and sections that drift from the page purpose.
Follow every semantic match back to its source page.
Example questions include: Show me internal linking opportunities, Audit this site, Where should I start?, Find pages competing for the same intent, What changed since the last crawl?.
Crawl a site, then ask what needs attention.
free to start