Galileo AI Evals

Galileo AI is a rare platform that genuinely bridges offline evaluation and online monitoring. Its key differentiator is the Luna model distillation—turning expensive LLM-as-judge evals into compact models that run in production at a fraction of the cost. This is especially valuable for high-throughput agentic systems where every millisecond and dollar counts. The out-of-box evaluators for RAG, agents, safety, and security cover the most common failure modes, and the auto-tuning feature ensures evals stay relevant as data drifts. The insights engine is also impressive: it not only detects hallucinations but prescribes fixes like adding few-shot examples. That said, the platform is clearly built for scale and enterprise rigor. Small teams with simple chatbots or basic prompt chains might find the setup complex and the cost prohibitive. If you only need basic monitoring, cheaper alternatives like LangSmith or open-source tools might suffice. But for teams rolling out AI agents in production with SLAs, Galileo’s eval-to-guardrail lifecycle is a standout capability that reduces risk and speeds up iteration. The ability to run guardrails on L4 GPUs and the support for VPC/on-prem deployment are strong signals for regulated industries. Caveat: pricing isn’t public, so you’ll need to book a demo—but given the enterprise focus, expect a per-signal or per-traffic pricing model.

Galileo AI is an AI observability and evaluation engineering platform designed to help teams stop AI failures before they impact users. It enables organizations to capture groundtruth data from synthetic, development, and live production sources, and build accurate, auto-tuned evaluations that outperform generic metrics. Galileo uniquely distills expensive LLM-as-judge evaluators into compact, low-cost Luna models that can monitor 100% of production traffic at 97% lower cost. The platform supports 20+ out-of-box evals for RAG, agents, safety, and security, plus custom evaluators to encode domain expertise. Galileo brings pre-production evals into production as guardrails without glue code, allowing eval scores to automatically control agent actions, tool access, and escalation paths. Trusted by enterprises like Writer, Cisco, NVIDIA, and MongoDB, Galileo integrates with existing ML stacks and offers deployment options including SaaS, Virtual Private Cloud, and On-Premises. Its insights engine analyzes millions of signals to identify failure modes, surface patterns, and prescribe fixes, accelerating debugging and deployment cycles. Unlike separate offline testing and online safety tools, Galileo unifies the eval-to-guardrail lifecycle for continuous AI governance.