Galileo

What is Galileo?

Galileo, now part of Cisco, is an end-to-end evaluation engineering platform that takes the guesswork out of LLM quality. It bridges the gap between offline testing and live production monitoring, giving AI teams a unified toolkit to capture ground-truth data, auto-tune evaluation metrics, and enforce guardrails across every prompt and response. What sets Galileo apart is its Luna model distillation technology. Instead of running expensive LLM-as-a-judge evaluations on every single production call — which quickly becomes cost-prohibitive — Galileo compresses those evaluators into tiny, low-latency models that run at a fraction of the cost (≈97% savings). This means you can monitor 100% of your traffic in real time without blowing your budget. The platform ships with 20+ out-of-box evaluation templates covering RAG quality, agent behavior, safety, and security. You can also build custom evaluators tuned to your domain. The auto-tuning engine continuously refines metrics from live user feedback, ensuring your evaluations stay relevant as your models and data evolve. For teams building AI agents, Galileo's insights engine is a standout feature. It analyzes millions of signals — traces, prompts, function calls — to surface hidden failure patterns like hallucinations, tool-selection errors, or drift. Better yet, it suggests fixes: add few-shot examples, tweak prompts, or adjust guardrails. Deployment is flexible. You can run Galileo as a managed SaaS, inside your VPC, or fully on-premises. Enterprise features include RBAC, SSO, custom rate limits, and dedicated support channels. The free tier (5,000 traces/month) makes it easy to start small, while Pro and Enterprise tiers scale with your needs. If you're building production-grade LLM applications and need observability that doesn't break the bank, Galileo deserves a close look.

How to Use Galileo

Getting started with Galileo is quick thanks to its generous free tier and extensive documentation. You can have your first evaluation pipeline running in minutes by following these simple steps.

Galileo Core Features

Galileo Use Cases

• 1AI Agent Debugging: Detect hallucinations, tool-selection errors, and multi-step failure modes in AI agents. Galileo's insights engine analyzes millions of traces to surface hidden failure patterns and provides automated fix recommendations, like adding few-shot examples when bad tool inputs cause errors in agent workflows.
• 2RAG & Retrieval Evaluation: Measure relevance, factuality, and citation quality of retrieval-augmented generation pipelines. Use out-of-box evaluation templates and auto-tuned metrics to ensure your RAG system delivers accurate, well-grounded responses that cite sources correctly.
• 3Safety & Security Guardrails: Block harmful, toxic, or policy-violating responses in real time using low-latency Luna models. Enforce guardrails across 100% of production traffic without the latency and cost overhead of running full LLM-as-judge evaluations on every request.
• 4Production Monitoring: Continuously evaluate every live inference to catch drift, bias, performance degradation, or unexpected failures. Galileo's insights engine flags anomalies early, allowing teams to intervene before issues impact end users at scale.
• 5Model Development & Iteration: Auto-tune evaluation metrics from real user feedback and feed insights back into training pipelines. This closes the loop between production monitoring and model improvement, enabling rapid iteration that keeps models aligned with real-world usage patterns.

Pros and Cons of Galileo

Galileo Pricing

Galileo FAQ

Galileo Review — Editor's Score

Galileo is a powerful end-to-end evaluation platform that stands out for its Luna model distillation technology and auto-tuning metrics. While pricing can scale steeply for large deployments and the enterprise tier requires sales contact, the free tier and Pro plan make it accessible for teams of all sizes. It's a strong choice for organizations serious about LLM quality in production.

• Luna model distillation reduces evaluation costs by ~97% while enabling real-time monitoring of 100% of production traffic.
• Auto-tuning metrics continuously adapt from live feedback, keeping evaluations aligned with real-world usage patterns.
• End-to-end workflow from ground-truth capture to production guardrails in a single unified platform.