The agent assembled a partial understanding of SanatanAI by combining direct site fetches with web search and competitor analysis, but encountered critical rendering gaps that left pricing and differentiation opaque. The homepage and routing structure exist, but the site does not publish pricing details in a machine-readable form, forcing the agent to rely on inferred context from the broader AI astrology market and the PujaPurohit ecosystem connection.

• ›Direct fetches of sanatanai.com (steps [1], [3], [8]) returned valid HTML but only shell structure; the Next.js app's content did not render in static fetch, so the agent extracted no pricing, feature details, or positioning language from the homepage or /pricing route.
• ›The agent successfully inferred core function (Vedic astrology + AI birth chart analysis) from metadata hints, page URLs (e.g., /how-it-works, /blog), and the PujaPurohit app store listing (step [19]), which revealed the company ownership and echosystem connection.
• ›Competitor research (steps [21], [25]) filled gaps by showing what feature transparency looks like in the category (KundliGPT, AstroSage, Ishvaram all publish free limits and methodology), making SanatanAI's lack of comparable transparency visible as a site design problem, not a limitation of the agent.
• ›The site's navigation structure exists (/pricing route returns 200) but does not expose pricing as static or meta-tagged content; the agent could not extract pricing tiers or cost details despite multiple fetch attempts, indicating the site requires client-side rendering or JavaScript execution to display critical commercial information.
• ›No third-party reviews, comparison articles, or press mentions of SanatanAI appeared in search results (steps [13], [29]); the agent had to default to comparing SanatanAI against better-documented competitors to provide relative positioning.