The agent successfully assembled a comprehensive overview of Nomagic's business by combining site fetches with web search and external sources, but encountered significant friction: the site's HTML responses were truncated and unreadable, forcing reliance on search results and third-party coverage. The agent built a coherent answer about what Nomagic does (Physical AI for warehouse automation), who it serves (large e-commerce/logistics), and how it differs from competitors, but could not find pricing details on the site itself—a major information gap the agent transparently flagged.

• ›The agent's initial fetches of nomagic.ai/ returned truncated HTML (4400+ chars truncated) that contained no readable content—making the homepage itself non-navigable for AI consumption. This forced the agent into a heavy web-search strategy to compensate.
• ›Pricing information was completely absent from the site (the /pricing route returned 404). The agent inferred the RaaS model from search results about the business model and the ASOS case study, not from site-published content. The agent explicitly called this out as 'confusing/missing.'
• ›The agent successfully discovered solution pages (/solution/picking, /solution/packing, /solution/sorting) via site-search queries, indicating the site does have navigable solution pages, but these pages' HTML was also truncated in the responses. The agent had to rely on search snippets and external sources (TechCrunch, CB Insights, ASOS case study) to populate details.
• ›The site failed to publish structured, machine-readable information in its HTML responses. The agent had to assemble facts from 56% web search and 33% prior artifact, indicating the site itself was largely opaque to automated reading.
• ›The agent cited seven external sources but only one nomagic.ai-owned page (ASOS case study, nomagic.ai/solution/picking, etc.) appeared in the final sources list. This reflects that most of the answer came from secondary sources, not from the primary site.