The agent successfully assembled a comprehensive explanation of tilit.ai's purpose, audience, pricing model, and competitive positioning by navigating the site's core pages and supplementing with web search results. However, the site's heavy JavaScript rendering meant the agent could not extract detailed content from the HTML alone and had to rely on prior knowledge and external search results to fill critical gaps—particularly around exact pricing, integration details, and the scope of their "comparison" feature. The final answer is substantive but acknowledges several information gaps that reflect the site's opacity on key commercial details.

• ›The homepage and main pages (steps [3], [5], [6], [7]) returned HTML that was heavily JavaScript-dependent; the agent could not extract meaningful content from the raw responses, forcing reliance on search and prior knowledge to synthesize the answer.
• ›The agent discovered core positioning (AI-powered automation for accountants and entrepreneurs, real-time reconciliation, no fixed costs) primarily through web search results (steps [9], [10], [15], [16], [17], [18]) rather than from directly fetched site content, indicating the site does not publish structured, machine-readable positioning on its pages.
• ›Specific pricing tiers, cost-per-unit figures, and the scope of the 'comparison' marketplace feature are not documented in publicly fetchable pages; the agent explicitly flagged these as missing and recommended direct contact with the company.
• ›The site appears to be a Next.js SPA that renders content client-side, making it difficult for the agent to extract information without JavaScript execution; this is a significant friction point for agent-readiness.
• ›The agent cited all six main pages it visited (steps [3], [5], [6], [7], [12]) as sources, but those citations reflect routing/discovery value rather than content extraction—the actual answer was constructed from search results and prior knowledge.