Use cases
Built for teams shipping LLM behavior into real workflows.
The product language stays grounded in actual deployment surfaces rather than generic AI dashboards.
AI support assistant
Track which prompt or policy changes create weak answers, thin responses, or slower resolution paths.
Internal copilot
Inspect the exact model output your operators saw instead of debugging from anecdote.
Workflow automation
Keep latency and response shape visible when chained LLM steps start drifting.
Retrieval-heavy QA
Reserve space for evals and regression review where grounding and completeness matter most.