The agent partially answered the task by assembling a coherent explanation of Madini's core offering (AI-powered mineral prospectivity mapping for African exploration) and its likely target market, but was unable to retrieve transparent pricing, detailed features, or competitive differentiation due to a JavaScript-rendered website that only exposed HTML boilerplate. The agent relied heavily on prior knowledge and web search snippets to fill gaps that the site itself did not surface in a machine-readable form.

• ›Step [9] search snippet confirmed Madini's name and domain focus (mineral prospectivity mapping) but did not include substantive product details; steps [18] and [20] web search results returned only index pages and unrelated competitor tools, not Madini-specific content. The site's own pages ([1], [3], [5], [6], [7], [11]) all returned identical HTML skeletons with no rendered content, making them non-content-bearing.
• ›The agent cited three external sources in its final answer (flypix.ai, gitnux.org, saiwa.ai) as supporting material, but these were general mineral exploration software guides, not Madini-specific documentation. No pricing, feature breakdown, or case study was retrieved or cited from madini.ai itself, forcing the agent to acknowledge in the final response that this information 'couldn't be found.'
• ›The website is fundamentally inaccessible to the agent's retrieval method: all direct fetches return only CSP headers and a Vite-rendered skeleton with no content payload. Pricing, features, and competitive positioning exist only in the JavaScript bundle and are not published in any server-rendered, API-accessible, or structured-data format. The agent could not determine whether pricing is public on the live site or genuinely unavailable.