The agent successfully gathered enough information to explain Flycode's core offering, pricing model, and differentiation, using the homepage, pricing page, and documentation. The site was reasonably navigable but lacked transparent pricing details and explicit competitor comparisons, forcing the agent to flag gaps rather than fill them with unsupported claims.

• ›Step [1] (homepage) provided the foundational value proposition and four product modules; steps [2] and [3] (pricing and homepage revisits) established the performance-based pricing model and AI-native differentiation claim.
• ›Step [5] (docs.flycode.com) added technical depth about how the platform works (ML model training, payment network data, supported integrations) but required the agent to type the URL from memory rather than following a link from the main site.
• ›The site explicitly contrasts itself against 'legacy solutions and PSPs' with static rule-based schedules, but does not name specific competitors—the agent correctly noted this as a missing element rather than inventing names.
• ›Pricing page provided only illustrative examples ($5M → $225K-$325K recovery) and emphasized 'personalized quote' requirement; the agent identified this transparency gap without claiming to have found a rate card that wasn't published.
• ›The agent assembled a coherent explanation of the product, pricing, and positioning from fragments across three main pages, demonstrating the site's content was navigable but dispersed and not always explicit about competitive positioning or implementation scope.