The agent assembled a partial but substantive picture of Nova's business by combining fetches from external news articles (Georgia Today, Forbes Georgia) with direct site access to the About Us page. The site itself proved poorly navigable for discovery: pricing, delivery, and competitor information remained completely inaccessible despite multiple search and direct-URL attempts, forcing heavy reliance on third-party journalism and prior knowledge to answer the task.

• ›Steps [11] and [13] (Georgia Today and Forbes Georgia articles) contained the most concrete, citable business information: employee count, manufacturing scope, brand partnerships (BETEK, IZOCAM, RIGIPS, INGCO), and market positioning. These were discovered via web search, not surfaced by nova.ge itself.
• ›Step [21] (nova.ge/en/about-us) returned HTML but the truncated response shows only boilerplate tracking and metadata — no visible text content in the snippet, suggesting the agent extracted little actionable detail from the site's own About page despite successfully fetching it.
• ›Critical e-commerce signals (pricing, delivery, shipping policy, local competitor names) were entirely absent from nova.ge's public pages. Direct URL guesses for /pricing and /about returned 404s. The site does not publish structured product data, reviews, or logistics info in agent-readable form.
• ›The agent's final answer relies heavily on prior knowledge (44% sourced) and web search results (44% sourced) rather than site content. This indicates nova.ge does not self-document its own value proposition, pricing model, or service terms in a way that agents can fetch and parse.
• ›Language barrier (Georgian-dominant site with partial English translation) compounded navigability: the agent noted that the English version has less content than the Georgian version, and site structure is not immediately obvious beyond search.