evoratec.com
partial
Claude Code
intent
What does evoratec.com do and who is it for? Explain it back to me.
24steps
115.0sduration
$0.8414cost
239,471tokens
31 steps7 reasoning steps6 searches
home
search
home
home
docs
search
/contacto
/wp-json/wp/v2/pages/7
/evomarket
/wp-json/wp/v2/pages/3…
search
/aviso-legal
search
/wp-json/wp/v2/pages/4…
/diseno-y-desarrollo-web
/wp-json/wp/v2/pages/4…
search
docs
/features
/wp-json/wp/v2/posts
/wp-json/wp/v2/pages
/wp-json/wp/v2/pages
search
/wp-json/wp/v2/pages
89%
on-site discovery
72%
reliability
67%
link following
path origin
- previous resource67%
- web search11%
- prior knowledge22%
insight
The agent partially understood Evoratec's business by assembling fragments from accessible pages (homepage, contact, EvoMarket demo, service pages), but could not find pricing, competitive positioning, or clarity on product maturity. The site lacks standard SaaS marketing elements—pricing pages, feature comparisons, testimonials—and forces visitors to contact the company for details, making it poorly navigable for agents seeking structured information.
- ›Step [5] (www.evoratec.com homepage) returned Elementor-rendered HTML that identified two service areas (web dev + EvoMarket) but provided no pricing or differentiation messaging; this was the primary content source.
- ›Steps [25] and [26] (WordPress REST API fetches of service pages) returned Elementor page data for 'Web Design' and 'Software Development' services, confirming the dual business model but offering no commercial details.
- ›Step [17] (EvoMarket page) revealed a demo environment with test payment card but no product pricing, licensing model, or feature specification—unclear whether it is a live commercial offering or portfolio project.
- ›Steps [13] and [29] (contact and design pages) repeatedly use 'contact us for details' patterns instead of publishing pricing or feature tables, indicating the site intentionally gates commercial information behind form submission.
- ›The site exposed no structured data (schema.org), no pricing API, no comparison tables, and no customer testimonials; the agent had to infer business model from page titles and descriptive text, making it low-readiness for agent discovery of purchasing intent.
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