Galileo AI

Galileo provides AI evaluation tools that detect hallucinations, measure response quality, and monitor LLM application performance. It offers real-time guardrails and automated quality metrics for RAG and agent systems.

Galileo is an AI observability and evaluation engineering platform designed to help organizations detect, diagnose, and prevent failures in large language model (LLM) applications. The platform enables teams to capture ground truth data from synthetic, development, and live production sources, including subject matter expert annotations, to create a living dataset that continuously grounds AI systems. It offers over 20 out-of-the-box evaluators for retrieval-augmented generation (RAG), agent, safety, and security use cases, and allows users to build custom evaluators to encode domain expertise. A key differentiator is the ability to distill expensive LLM-as-judge evaluators into compact, low-latency, low-cost Luna models that can monitor 100% of production traffic at significantly reduced cost.

The platform provides real-time guardrails that transition offline evaluations into production safeguards. Its insights engine analyzes agent behavior to identify failure modes, surface hidden patterns, and prescribe fixes, enabling rapid debugging and faster deployment cycles. Galileo ingests signals from models, prompts, functions, context, datasets, traces, and MCP servers, and supports a range of evaluation types including hallucination detection, response quality measurement, and performance monitoring for LLM applications. The platform is positioned as an enterprise-grade solution trusted by enterprises and developers alike, with a freemium pricing model that offers a free tier for getting started.

Galileo is primarily focused on text-based LLM applications, including RAG systems and agent architectures. The website content does not indicate support for image, video, or audio inputs or outputs. The platform appears to be a SaaS offering, with documentation, pricing, and resources available on its website for further exploration.