The agent successfully assembled a comprehensive explanation of Rig's positioning, target market, platform architecture, and differentiation, working around significant gaps in transparent pricing and feature documentation. The site is moderately navigable for discovery purposes but relies heavily on marketing copy rather than structured, machine-readable data; pricing was opaque and forced the agent to flag uncertainty as a notable limitation.

• ›The homepage [0], pricing page [1], comparison page [6], platform page [12], and case study [11] collectively provided positioning, differentiators, and use-case clarity, but each returned marketing narratives rather than structured specifications—no schemas, pricing tables, or API docs that would make the information machine-readable.
• ›Pricing information was notably absent: step [1] returned a pricing page but only described pricing *structure* (platform + usage fees, tiered by deployment) without publishing actual costs, forcing the agent to flag this as a transparency gap and limiting the ability to satisfy the 'how it's priced' requirement completely.
• ›The agent discovered solution-specific pages [10: startups] and case studies [11] by following links from the site's own navigation, but had to rely on web search [4, 5, 9] and prior knowledge to surface the comparison page [6]—indicating the site's internal linking does not surface all key decision-support pages equally.
• ›Feature boundaries were vague from the rendered HTML: the agent noted that 'exact feature boundaries' and 'Data Apps' capabilities were unclear because the site uses JS-heavy rendering and marketing-speak rather than a documented feature matrix or capability table.
• ›The site provides no quantitative limits (data volume, query latency, scaling thresholds) or structured integration metadata—the agent had to resort to citing external DEV.to content [referenced in final sources] to explain MCP integration, indicating docs are fragmented across the domain.