AI Observability & Evaluation
LangSmith, Arize, Braintrust, Galileo
As enterprises move agents to production, LLMOps/eval platforms (LangSmith, Arize, Braintrust, Galileo, Weights & Biases) monitor quality, cost, drift, and hallucination. Regulated verticals require this evidence trail for audit and model-risk governance.
Examples
LangSmith, Arize, Braintrust
Driver
Audit & model-risk governance
How it fits the stack
AI Observability & Evaluation with what it depends on (above) and what it feeds (below). The figure renders as a crawlable diagram and upgrades to an interactive 3D graph as it scrolls into view.
AI Observability & Evaluation in the AI stack. AI Observability & Evaluation with its immediate upstream dependencies (top) and downstream dependents (bottom) in the AI value chain. Hover a node in 3D, or read the full relationships below.
Graph data (text) — 3 entities, 2 relationships
- Financial Services AI —depends on→ AI Observability & Evaluation
- NIST AI Risk Management Framework —uses→ AI Observability & Evaluation