The agent successfully gathered enough information to explain what ACTAVA does, who it's for, and how it differs from alternatives, but encountered a critical gap: public pricing information does not exist on the site. The agent assembled its understanding primarily from the homepage, customer stories page, a detailed blog post, and external third-party comparisons (Kore.ai), since ACTAVA's own website does not publish pricing, detailed feature documentation, or competitive positioning in a machine-readable or easily fetchable form.

• ›Step [1] (homepage) was fetched but returned only HTML scaffolding—the actual content was client-side rendered via Next.js, making it impossible to extract full feature/value propositions directly from the page source.
• ›Step [7] (blog post 'Healthcare Has an AI Deployment Problem...') was the most substantive content-bearing resource, providing concrete context about workflow automation, policy-richness, and the problem ACTAVA solves.
• ›Step [6] (customers page) confirmed target customers (Johns Hopkins, Momentum Actuarial, ThoroughCare) but did not provide pricing or detailed use case specifics.
• ›Step [12] (external Kore.ai comparison) was critical for understanding ACTAVA's competitive differentiation—the agent had to rely on a third-party analyst guide because ACTAVA itself does not publish direct competitor comparisons.
• ›The pricing page (step [3]) returned 404, forcing the agent to acknowledge this as unfindable rather than incomplete. No alternative pricing discovery path (e.g., demo request forms, contact pages with pricing hints) was available.
• ›The agent relied heavily on web search (67% of fetch sources) and prior knowledge (17%) to fill gaps, indicating the website itself is not self-contained enough to answer the full question without external context.