Production Readiness Gate

The Production Readiness Gate treats evaluation as a contractual checkpoint rather than a post-launch cleanup task. Before any AI feature touches a client's live environment, it must clear a defined bar: traced agent behavior, scored response quality, and drift detection running on real traffic. Agencies that formalize this gate can price AI work as production-ready delivery instead of experimental builds, because the gate produces evidence the client can audit. The gate also caps downside: when an agent misbehaves, the trace log shows exactly which span failed and when, which shortens incident reviews from days to hours. A voice agent deployment illustrates the pattern well. Cekura simulates thousands of personas before go-live, then monitors live calls for gibberish, interruption, and latency signals, so the agency hands over a system with a documented pass record rather than a demo. Langfuse and Confident AI serve the same gate function for text and multi-model stacks.