The agent assembled a functional understanding of NGT Servicios by combining site navigation (homepages, project pages) with sitemap discovery, but could not locate pricing information despite explicit searching. The site is navigable in structure but minimally agent-friendly: it publishes no pricing, no differentiator statements, and no clear sales pathway; most content is JavaScript-rendered and text-sparse, forcing the agent to rely on project case studies and URL patterns to infer what the company does.

• ›The agent successfully fetched and used homepage and project pages (steps 1, 3, 9, 20–22, 30, 37), which returned HTML with metadata and styling but truncated/hidden actual text content due to Next.js client-side rendering—the agent could not extract page body text directly from responses.
• ›The sitemap (step 17) and robots.txt (step 18) were critical routing artifacts that revealed the site structure (/es/proyectos/*, /es/brief, /es/privacidad) but contained no content themselves; the agent followed these breadcrumbs to find actual project pages.
• ›Pricing and competitor differentiation were completely absent from the site: no /precios, /pricing, /planes, or /comparacion pages existed; the agent's web search (steps 24, 35) also returned zero results for pricing on this domain, confirming no public pricing is indexed.
• ›The agent inferred business model and value prop from indirect signals: project case-study URLs (TallerPro, Trayectoria, Orhize-Pilates, Kiki-Estampado) suggested service verticals; a Spanish-language focus implied Latin American market; the mention of 'no monthly fee' in TallerPro (likely extracted from prior knowledge or page snippets) was the only pricing signal found.
• ›Contact/sales friction is high: no visible CTA, no 'get quote' button, only a 'brief' intake questionnaire with unclear location/submission mechanism in the final response.
• ›The site's bilingual structure (/es and /en) is declared in sitemap and hreflang but English pages return the same truncated HTML; no semantic markup (JSON-LD, microdata) was present in fetched responses to help agents parse structured business information.