The agent successfully gathered comprehensive information about Cohesivity by visiting the homepage, about page, docs index, pricing, offerings catalog, and agent reference documentation. The site is well-navigable for an agent seeking to understand the product — it publishes structured, machine-readable documentation (including agent-specific llms.txt) that directly answered all four questions (what they do, who it's for, how it's priced, how it differs). The agent identified specific gaps in competitive positioning and pricing details but assembled a complete, accurate explanation from the available sources.

• ›Step [1] (homepage) and step [2] (about page) provided clear positioning: 'backend infra for AI agents' with explicit mention of agent-first design and the core value proposition (one API vs. multiple provider signups). These were the primary sources for 'what they do' and 'who it's for.'
• ›Step [4] (pricing page) was content-rich and directly answered pricing structure — all four tiers with specific credit amounts and bucket limits were fetched and cited verbatim. This step was essential and complete.
• ›Step [5] (offerings catalog) and step [6] (llms.txt) provided agent-focused documentation; step [6] is a dedicated LLM-facing artifact that the agent likely used to understand positioning vs. alternatives (agent-native design, MCP, one API philosophy). These steps confirmed the site's agent-readiness.
• ›The site publishes llms.txt explicitly for agents; the agent fetched it (step [6]) and used it to infer differentiation. However, the site does NOT publish explicit competitive comparisons — the agent had to infer 'how it's different' from implicit design choices mentioned across docs.
• ›Pricing details are complete and transparent on the pricing page; however, some resource-specific costs (domain registration via Razorpay, Steel Browser tiers) were mentioned but not fully detailed, which the agent correctly flagged as 'confusing or missing.'
• ›The site's navigation is straightforward for agents: docs index (step [3]) clearly links to pricing, offerings, and agent reference docs, enabling the agent to locate all necessary information in a linear path.