shaed.ai
success
Claude Code
intent

What does shaed.ai do and who is it for? Explain it back to me.

19steps
72.6sduration
$1.1169cost
129,889tokens
24 steps5 reasoning steps9 searches
home
docs
docs
/features
search
docs
/news-releases/shaed-u…
/shaed
search
/ar/technology/startup…
search
search
search
search
search
/company/shaed
search
/companies/shaed
search
40%
on-site discovery
90%
reliability
30%
link following
path origin
  • previous resource30%
  • web search60%
  • prior knowledge10%
insight

The agent gathered a comprehensive explanation of SHAED's business, positioning, and backing through web search and third-party business intelligence sources, but could not complete the task on pricing and detailed customer information. The shaed.ai website itself is a React SPA that serves only minimal meta tags to server-side fetches—all meaningful content required external sources (press releases, CB Insights, Dealroom, Auto Remarketing). The agent successfully synthesized what was publicly available into a clear explanation, but had to acknowledge significant gaps (pricing is completely opaque, customer case studies unavailable) that would require direct sales contact.

  • ›Steps [1–4] fetched the homepage and attempted navigation to /pricing, /about, /features but returned only boilerplate HTML—the site is a React app that doesn't render content server-side, making it unreadable to the agent without JavaScript execution.
  • ›All substantive content came from external sources: step [10] (PR Newswire press release with funding, company founding, and platform capability overview), step [13–14] (search results pointing to third-party summaries), step [16] (CB Insights company profile with competitor context), step [18] (Auto Remarketing article with procurement pain-point narrative), step [21] (search result pointing to EnerTech Capital investment post).
  • ›Pricing information was explicitly not found anywhere—no press releases, no third-party reviews, no case studies with ROI metrics published. The agent correctly called this out as a gap and reasonably inferred enterprise custom pricing based on the B2B SaaS pattern.
  • ›The site's own marketing surface (homepage, /pricing, /about, /features URLs) failed to deliver content to a server-side fetch, forcing 100% reliance on external discovery and business intelligence sources. This is a critical accessibility gap for agent navigation.
  • ›The agent cited 6 sources in the final response, all discovered via web search or guessed URLs—none came directly from the shaed.ai website itself. This represents a site-to-agent misalignment: the company has information to share but hasn't published it in a fetch-friendly format.

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