Scope

Scope is an early-stage agent experience platform addressing a real blind spot: how AI agents interact with your product. Traditional analytics track humans—page views, clicks, funnels—but agents behave differently: they parse docs, call APIs or tools, and silently fail when they hit friction. Scope simulates the full agent journey—discovery, understanding, task completion—and captures what the agent saw, tried, skipped, and why. The reasoning logs are a standout: they give you the agent's internal rationale for each decision, so you can see, for example, why it chose a competitor or abandoned an install. Where Scope excels is in diagnostics. If your product has an install error, a doc mismatch, or a broken flow that only agents hit, Scope won't just tell you something is wrong—it will suggest concrete fixes, like updating an endpoint description or clarifying parameter docs. This is a proactive approach: you don't wait for support tickets; you catch friction daily. However, Scope is early access. Expect rough edges and a learning curve. It requires engineering involvement to implement recommendations, and its effectiveness depends on accurate simulation, which may not mirror every real-world agent. Pricing isn't public—you must contact sales, which can be a hurdle for smaller teams. For companies already seeing agent traffic, Scope is a smart investment to optimize agent-driven revenue. For those without agent usage yet, it might be premature; focus on making your product agent-friendly first. Alternatives like PostHog or Langfuse offer basic LLM observability, but they don't simulate agent behavior or provide reasoning logs. If agents are part of your growth strategy, Scope is worth a demo.