Overview
What Is Galileo?
Galileo’s evaluation and observability platform empowers developers to evaluate and improve their AI apps and agents. Use Python or Typescript SDKs to easily add evals directly into your code, gather insights, apply run-time guardrails, and improve AI reliability.
Galileo simplifies this process by providing metrics to evaluate, improve, and continuously monitor the performance of your generative AI applications. With Galileo, teams can quickly identify blind spots, track changes in model behavior, and accelerate the development of reliable, high-quality AI solutions.
When building AI applications, even when you feed the exact same input into your system, you might receive a range of different outputs, complicating the process of defining what “correct” even means. This variability makes it difficult to establish consistent benchmarks and increases the complexity of debugging when something goes awry.
Moreover, as the underlying models and data are updated and evolve, application behavior can shift unexpectedly, rendering previously successful tests obsolete. This dynamic environment requires tools that not only measure performance accurately but also adapt to ongoing changes, all while providing clear, actionable insights
into the AI’s behavior across its entire lifecycle.
Log your first trace
Learn how to log your first trace with Galileo
Evaluate your first trace
Learn how to evaluating metrics for your first trace with Galileo, and improve your application
Sample projects
Learn how to get started with the Galileo sample projects that are included in every new account.
Contact us
Got questions? Contact us to schedule time to learn about our evaluation platform.
Stay up to date: Check our Release Notes for the latest features and improvements.
The challenge
AI applications introduce a unique set of challenges that traditional testing methods simply cannot address.
How Galileo helps
Identify issues with powerful metrics
Pinpoint problems instantly with built-in and custom metrics. Get analytics across correctness, completeness, safety, and relevance dimensions. Use token-level highlighting to diagnose root causes and implement targeted fixes.
Run experiments with structured datasets
Evaluate your AI with organized datasets targeting specific scenarios and edge cases. Build regression test suites, compare performance across inputs, and track improvements over time to prevent regressions.
Test and compare multiple approaches
Compare models, prompts, and configurations side-by-side with quantifiable metrics. Run controlled tests to measure the impact of changes and make data-driven decisions when optimizing your AI systems.
Stop prompt attacks, data leaks, and hallucinations with runtime protection
Deploy runtime protection in production. Get immediate visibility into model behavior and set thresholds that maintain quality and safety in your live AI systems.
Features
Galileo delivers essential tools for AI development - from evaluation metrics and RAG-specific tools to a robust experimentation framework. Everything you need to build, test, and maintain high-quality AI systems throughout their lifecycle.Luna-2 Evaluation model
Discover Galileo’s Luna-2 Evaluation model, reducing the latency and cost for metric evaluations.
Data-driven metrics
Automated, token-level quality checks to reveal nuanced performance insights. Understand exactly how your AI is performing with detailed analytics.
Configurable regression detection
Tolerance thresholds that filter out minor fluctuations, highlighting significant issues. Get alerted only when changes matter to your application.
Integrated feedback
Seamlessly incorporates real-world insights into your development cycle. Turn user feedback into actionable improvements for your AI system.
End-to-end visibility
Clear, visual tracking of your AI application’s performance—from prompt design to production. Monitor the complete lifecycle in one unified interface.