Platform & Infrastructure
AI Observability
See what your AI actually did, what it cost and where quality is slipping.
How we approach it
Tracing, evaluation and cost attribution for AI systems. Conventional monitoring says a request succeeded; it cannot say the answer was wrong. This is the tooling that catches quality regressions before customers report them.
What you get
- Full traces of prompts, retrievals and tool calls
- Automated evaluation against a regression set
- Cost attributed by feature, tenant and model
- Alerts on quality drift, not just errors
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