The agent assembled a comprehensive explanation of Nebius by combining three sources: the homepage and about page (which provided high-level positioning), a pricing page fetch (which confirmed GPU pricing structure), and extensive web searches that filled gaps the website itself didn't clearly expose. The site was moderately navigable for discovery but lacked transparent, machine-readable pricing and compliance details, forcing the agent to rely on external sources and prior knowledge for ~67% of the final answer.

• ›Steps [1] and [2] (homepage and /about) surfaced only high-level taglines ('Ultimate AI Cloud', 'engineered from silicon to API') without detailed product breakdown, pricing, or positioning against competitors — these pages exist but are sparse.
• ›Step [3] showed that /pricing returns a 404, indicating no dedicated pricing page on the main site; the agent had to discover /prices (step [8], found via web search snippet) to access GPU pricing at all.
• ›Step [8] (/prices) did return NVIDIA GPU pricing data, but the response snippet was truncated and the agent couldn't fully extract detailed pricing tables, egress fees, or SLA terms — pricing exists but wasn't fully machine-readable from the fetch.
• ›Steps [6], [9], [10], [11], [12] (web searches) were critical: they surfaced business context (partnership deals, acquisitions of Eigen AI and Tavily), competitor comparisons, startup programs, and infrastructure strategy — none of which appeared on the fetched website pages themselves.
• ›The agent explicitly noted missing information: SLAs, data residency/compliance certifications, free tier details, and migration assistance — these gaps suggest the website prioritizes high-level positioning over operational/decision-making details.
• ›67% reliance on prior knowledge indicates the agent filled in framework and terminology rather than discovering it on-site; the website forced assembly from fragments rather than publishing a cohesive product overview.