digitalapplied.com
success
Claude Code
intent

What does digitalapplied.com do and who is it for? Explain it back to me.

13steps
72.7sduration
$0.8313cost
116,048tokens
21 steps8 reasoning steps5 searches
home
docs
docs
/services
search
docs
search
docs
search
/work
search
/faq
search
100%
on-site discovery
63%
reliability
50%
link following
path origin
  • previous resource50%
  • prior knowledge50%
insight

The agent assembled a comprehensive overview of Digital Applied by combining content from the homepage, about page, services page, and blog — but had to work around a site with limited machine-readable structure and missing key pages (pricing, FAQ, case studies all returned 404s). The agent succeeded at the discovery-evaluation task by synthesizing fragments from fetched pages and prior knowledge, but the lack of a dedicated pricing page, case studies, or structured data meant the final answer relied heavily on inference and piecing together mentions across blog content and search metadata.

  • ›Step [1] (homepage) and step [5] (services) were the primary content sources, but the HTML responses were truncated in the trajectory log, indicating the agent extracted information from rendered content that wasn't explicitly surfaced in the fetches shown. The agent cited these pages as sources but the actual content bearing their claims about 'nine services,' unit economics, and deliverables is not visible in the trajectory.
  • ›Step [4] (about page) and step [8] (blog index) were fetched but likewise truncated, yet the agent drew on them to construct claims about the business model, team structure ('rebuilt around AI agents'), and positioning — suggesting the site publishes this information but not in a format easily captured or verified from the log.
  • ›Critical pages returned 404s: /pricing (step [3]), /faq (step [14]), /work (step [11]) — forcing the agent to infer pricing details (€100/unit, €2K minimum) from blog articles and search results rather than a primary source. This fragmentation weakened the final answer's authority on pricing and social proof.
  • ›The agent relied on web search results (steps [7], [10], [16], [19]) to surface blog URLs and external third-party mentions of Digital Applied's positioning, but search snippets were themselves truncated in the trajectory. The agent's synthesis of 'nine services' and 'transparent unit-based pricing' appears to come from partial knowledge rather than complete page reads.
  • ›The site is not agent-ready for this task: no structured data (schema.org), no /pricing page, no /case-studies or /testimonials page, truncated HTML responses, and key differentiators scattered across a blog rather than consolidated on a primary page. The agent had to compensate with extensive searching and prior knowledge (marked at 50% sourcing).

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