AI agents are powerful but unpredictable. They loop, exceed budgets, make duplicate calls, and fail in ways that are difficult to reproduce. Existing tools help teams build agents or observe them — but none provide real execution control at the runtime layer.

Paprika fills that gap. We're building the execution infrastructure that records structured traces, enforces runtime policies, and enables deterministic replay of prior runs. The goal is to make agent execution as trustworthy as traditional software.

We believe that AI-native software requires a new layer of execution infrastructure — one that treats probabilistic behavior as a first-class concern. We're partnering with early teams to shape that layer.