The agent gathered a partial understanding of Quaerion by combining web search results with fetches from their main website and blog, but the site's JavaScript-heavy architecture and lack of public pricing/case studies limited direct content retrieval. The agent successfully explained Quaerion's core service (Answer Intelligence consulting), target market positioning, and methodology, but could not locate specific pricing, client examples, or detailed service tiers—requiring the agent to acknowledge gaps and work around inaccessible content.

• ›Steps [7] and [8] (fetches of quaerion.com.br/ and /solucoes) returned Next.js-rendered HTML but were heavily truncated (4400+ chars omitted), preventing the agent from extracting rendered content; the agent had to infer from metadata and search results instead.
• ›Step [16] (blog post on GEO optimization) similarly returned truncated Next.js HTML, suggesting the site's content is client-side rendered and not easily machine-readable in static fetch form.
• ›Step [24] (search result mentioning 'primeira startup Answer Intelligence') and the earlier search results in steps [5], [11], [13] provided the semantic scaffolding (AEO, AIO, GEO acronyms, positioning claims) that the agent used to construct its explanation, but these were sourced from external educational articles and the search index, not directly from Quaerion's own pages.
• ›Pricing, client case studies, team information, and specific service tiers were never found in any step, indicating the site either does not publish this information publicly or it is gated/JavaScript-rendered in a way that prevented discovery.
• ›The agent relied heavily on web search (60%) to fill gaps that the site's own fetches could not satisfy, suggesting Quaerion's website is not agent-friendly for direct content extraction.