The agent successfully assembled a comprehensive explanation of OneTrust by combining sparse direct site content with third-party sources. OneTrust.com itself provided only basic scaffolding (homepage, products, platform, pricing page links) but no substantive detail; the agent had to rely on web searches and external articles (Enzuzo, Shopify, TrustArc) to answer what OneTrust does, who it's for, pricing ranges, and how it compares to competitors. The site's lack of transparent pricing, detailed product segmentation, and case studies forced heavy dependence on prior knowledge and search-sourced intelligence.

• ›OneTrust.com's own pages (steps 1–7) returned only HTML scaffolding with metadata; no substantive content was extracted from the direct site fetches. The pricing page exists but contains no actual tier or cost data.
• ›The agent discovered that OneTrust deliberately does not publish pricing transparently—requiring 'contact sales' instead. This design choice made the site unnavigable for the core question (how it's priced) and forced reliance on third-party market research (Enzuzo, Vendr, CheckThat) that aggregates pricing from 300+ customer reports.
• ›Key facts about OneTrust's positioning (14,000+ customers, 75 Fortune 100 clients, 6+ modules, AI governance focus) were not found on the official site. Steps 13 and 15 (Enzuzo and TrustArc articles) provided the competitive context and feature clarity that onetrust.com itself did not surface.
• ›The site is poorly structured for agent discovery of differentiators: no published competitor comparison table, no ROI case studies accessible without sales contact, no clear module/tier segmentation for different buyer personas, and no free trial pathway. The agent had to work around these gaps entirely.
• ›44% of the agent's knowledge came from previous_artifact (likely cached fetches or prior runs), suggesting OneTrust.com is a known-poor information source that agents default to supplementing with external research.