The agent assembled a comprehensive overview of candis.io by combining web search results with attempted direct site fetches, ultimately satisfying the task despite the site's client-side rendering architecture making direct HTML inspection unproductive. The site proved poorly navigable for machine agents—pricing and features pages returned 404s, forcing reliance on search engine results and prior knowledge to construct the answer.

• ›Direct site fetches (steps [1], [4], [6], [11]) returned Next.js-rendered HTML with no readable content—the agent correctly recognized this limitation and pivoted to search. Web searches (steps [8], [9], [12]) yielded actual information: search snippet titles revealed the pricing page URL (/en/price) and competitor landscape, which the final response cited explicitly.
• ›The site's routing is broken for standard paths: /pricing and /en/pricing both returned 404s (steps [2], [5]), yet search results revealed the correct URL is /en/price—a discoverability failure that forced the agent into web search rather than native site exploration.
• ›The agent's final answer was substantially sourced from search results and prior knowledge (~67% per sourcing metadata), not from the site's own content. Pricing details, feature positioning, and competitor analysis came from third-party review sites (Crunchbase, SaaSHub, G2, SoftwareSuggest) rather than candis.io's own documentation. The site did not publish machine-readable comparisons, pricing matrices, or structured data that would allow direct extraction.
• ›The agent acknowledged several information gaps (specific pricing tiers, feature comparison, implementation timelines, free trial limits)—these were genuinely absent from both the site and public search results, indicating candis.io does not publish this level of detail publicly.