The agent partially satisfied the discovery-evaluation task by assembling a coherent overview of Reze from web search results and a note.com article, but the landing page itself (lp.reze.app) was not agent-navigable — it returned React markup without readable content, and direct attempts to access pricing and features pages returned 404s. The agent relied heavily on web search and prior knowledge to reconstruct what Reze does, who it's for, and how it differs from competitors, but could not find pricing information despite multiple targeted searches.

• ›The landing page at lp.reze.app/ returned raw Next.js HTML/React code that the agent could not parse for content; the site is client-rendered and not statically readable by fetching the initial response.
• ›Dedicated pages (/pricing, /features) returned 404 errors, indicating the site either uses client-side routing exclusively or does not expose these sections publicly — this forced the agent to rely entirely on external sources.
• ›Step [3] (initial web search) and step [14] (note.com article fetch) were the primary sources of substance, providing context on Reze's purpose, AI automation focus, and market positioning; note.com hosted more detailed editorial content than the landing page itself.
• ›Pricing remained opaque throughout: no public rate cards, tier comparisons, or cost-per-metric information appeared in any fetched or searched resource, only indirect mentions of 'contact for quotes' and one reference to partial free features.
• ›Competitor research (steps [15], [11]) required web search for Japanese medical billing system comparisons (ORCA, Fujitsu, etc.) because the landing page does not acknowledge or differentiate against alternatives.
• ›The agent successfully inferred target market (Japanese hospitals/clinics) and core value proposition (AI-powered automation of medical billing) from fragmented sources, but had to synthesize rather than extract from a single authoritative on-page source.