AI MONITORING & OBSERVABILITY · SECOND LAYER
AI Monitoring.
Every AI call observed. Cost, FinOps, usage, user feedback and guardrail alerts in one dashboard, across every app and provider — the operational side of Kosmoy's AI Monitoring & Observability layer.
When AI runs across many apps, teams and providers, the only way to manage it is to see every call. Kosmoy logs them all and breaks the picture down by app, team, model, use case and time.
Cost is usually the first question — frontier-vs-small-model spend can be two orders of magnitude apart. Quality is the second — user feedback connects to prompts and models. Risk is the third — guardrail alerts roll up the same way.
This is the operational side of Kosmoy’s AI Monitoring & Observability layer — the FinOps and live-quality view. Its companion is AI Evaluation & Red Teaming, which scores quality, groundedness, tool use and safety offline and online and attacks the system to establish what it can be made to do. That evaluation side is the slice Gartner calls AI evaluation and observability; monitoring and FinOps here are broader than Gartner’s category and complete the layer.
Module questions, answered straight.
What does AI Monitoring actually log?
Every LLM, MCP and agent call routed through Kosmoy — prompt, model, latency, cost, user feedback, guardrail event. Broken down by app, team, model, use case and time.
Can it see calls that don't go through the Gateway?
No. Calls made directly to a model provider don't appear in the dashboard. The remediation is to bring the call into the Gateway path.
How does it integrate with our observability stack?
Kosmoy emits structured events that ship to Splunk, Datadog, Grafana, Snowflake and similar pipelines. The Insights Dashboard is the AI-native view; your APM stack stays the long-horizon home for cross-correlation.
See AI in production, not just AI in pilots.
Walk through the dashboard with real cost, quality and risk data.