alloia.ai
success
Claude Code
intent
What does alloia.ai do and who is it for? Explain it back to me.
8steps
40.5sduration
$0.2277cost
24,560tokens
14 steps6 reasoning steps
home
docs
home
/product
docs
/features
docs
docs
83%
answer from your site
50%
answer efficiency
71%
followed site links
answer sources
- from this site83%
- from agent knowledge17%
url discovery
- given in the task13%
- followed a link63%
- guessed the URL25%
insight
Agent successfully gathered enough information to explain Alloia's core value proposition, pricing, and differentiation from the homepage, pricing page, and blog. The site is navigable but incomplete—no dedicated features, product, or about pages, and enterprise pricing is not disclosed; the agent filled these gaps by synthesizing what was available and flagging what was absent.
- ›Steps [1] and [4] (both homepage fetches) provided the bulk of substantive content: what Alloia does, who it's for, and how it differs. The agent had to fetch the same URL twice, suggesting the homepage is the primary information hub and the site lacks dedicated landing pages for features, product details, or company information.
- ›Step [3] (pricing page) was straightforward and complete: two tiers with clear pricing, commitment terms, and feature lists. This page directly answered a core task requirement without ambiguity.
- ›Step [10] (blog) provided conceptual depth by introducing Generative Engine Optimization (GEO) as the framing device, but contained no new pricing, feature, or competitor comparison details. The blog reinforced positioning rather than expanding the core offer.
- ›Four attempted URLs returned 404 (features, product, docs, about), indicating the site does not expose these common information structures. The agent had to work with only homepage, pricing, and blog—a thin surface area.
- ›The agent could not find explicit competitor comparisons or detailed enterprise pricing, and flagged these gaps in the final response. No search queries were used; all discoveries came from direct URL guessing or homepage links, meaning the information hierarchy depends entirely on site structure and the agent's assumptions about standard URL patterns.
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