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ai deep-dive

Galileo Deep Dive: Experiments, Evaluators, and the Agent Observability Loop

Galileo connects dataset experiments, LLM/code/Luna evaluators, production traces, and runtime guardrails. It fits enterprises that need observability plus intervention, but the old Protect surface is deprecated and evaluator models do not replace human calibration or application security.

#galileo-ai#llm-evaluation#ai-observability#llm-as-a-judge#experiments#guardrails
ai deep-dive

Patronus AI Deep Dive: From Evaluators and Experiments to Production Monitoring

Patronus AI treats evaluators as reusable scoring units, then applies them to offline experiments and production traces. It suits teams that want managed hallucination, safety, and multimodal evaluators, but judge scores cannot replace human labels, deterministic tests, or real security validation.

#patronus-ai#llm-evaluation#llm-as-a-judge#ai-safety#observability#experiments