Galileo is a cutting-edge evaluation and observability platform designed to empower developers building advanced generative AI solutions, such as RAG and AI agents. Traditional AI evaluation tools often fall short when dealing with the unpredictability of LLMs, making debugging of hallucinations notoriously challenging.
Get up and running for free with a few lines of code.
Got questions? Contact us to schedule time to learn about our evaluation platform.
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.
Stay up to date: Check our Release Notes for the latest features and improvements.
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.
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.
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.
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.
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.
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.
Discover Galileo’s Luna 2 Evaluation model, reducing the latency and cost for metric evaluations.
Automated, token-level quality checks to reveal nuanced performance insights. Understand exactly how your AI is performing with detailed analytics.
Tolerance thresholds that filter out minor fluctuations, highlighting significant issues. Get alerted only when changes matter to your application.
Seamlessly incorporates real-world insights into your development cycle. Turn user feedback into actionable improvements for your AI system.
Clear, visual tracking of your AI application’s performance—from prompt design to production. Monitor the complete lifecycle in one unified interface.
Galileo is a cutting-edge evaluation and observability platform designed to empower developers building advanced generative AI solutions, such as RAG and AI agents. Traditional AI evaluation tools often fall short when dealing with the unpredictability of LLMs, making debugging of hallucinations notoriously challenging.
Get up and running for free with a few lines of code.
Got questions? Contact us to schedule time to learn about our evaluation platform.
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.
Stay up to date: Check our Release Notes for the latest features and improvements.
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.
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.
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.
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.
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.
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.
Discover Galileo’s Luna 2 Evaluation model, reducing the latency and cost for metric evaluations.
Automated, token-level quality checks to reveal nuanced performance insights. Understand exactly how your AI is performing with detailed analytics.
Tolerance thresholds that filter out minor fluctuations, highlighting significant issues. Get alerted only when changes matter to your application.
Seamlessly incorporates real-world insights into your development cycle. Turn user feedback into actionable improvements for your AI system.
Clear, visual tracking of your AI application’s performance—from prompt design to production. Monitor the complete lifecycle in one unified interface.