Scope

Scope’s core insight is that when an AI agent fails to use your product, the buyer never reaches your funnel—and that failure is invisible in web analytics. The platform addresses this with daily automated simulations that exercise your real user workflows, capturing tool calls, latency, errors, and the agent’s reasoning. This reasoning log is the standout: it tells you why an agent picked a competitor or skipped a feature, not just that it did. Usage friction detection—install errors, doc mismatches, broken flows—is concrete and actionable, and Scope suggests precise fixes "done for you today." Scope also evaluates AI search visibility, a growing discovery channel for agent-driven buying. The full-stack approach means it covers everything from discovery to task completion. On weaknesses, the product is early access, so expect gaps in coverage and a dependency on accurate simulation—real-world edge cases may slip through. There’s no public pricing, so you’ll need to book a demo to evaluate cost. Implementation requires engineering resources to act on recommendations, so it’s not for teams without that capacity. For teams already seeing agent traffic, Scope is a proactive alternative to reactive log analysis—it catches failures before they cost deals.