What is Galileo?
Galileo is an AI evaluation and observability platform built specifically for developers building complex AI applications. It addresses the inherent challenges of generative AI—where the same input can yield different outputs—making it hard to pin down quality and troubleshoot issues.
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The Challenge
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.
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.
Protect Applications with Runtime Guardrails
Deploy real-time guardrails 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.
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.