Follow every request
Follow the request through application code, retrieval, models, tools, queues, and external systems.
You get a working system with explicit quality boundaries — not a model call wrapped in a polished interface.
Follow the request through application code, retrieval, models, tools, queues, and external systems.
Connect test scores and user outcomes with speed, cost, errors, and releases.
Alerts include the context needed to explain, reproduce, and fix the failure.
We start with the behavior and operating constraints that matter, then make each release measurable and reversible.
Define trace boundaries, attributes, correlation IDs, redaction, and sampling.
Dashboards answer real operating questions instead of showing disconnected numbers.
Confirm live tracking data and metrics actually arrive, then rehearse failures and alerts.
Bring the current build, the workflow, or the production problem. We will map the shortest responsible path forward.
See what your AI system is doing in production: prompts, answers, tool use, speed, cost, errors, and what users actually get.