Keywords AI

Galileo AI vs Ragas

Compare Galileo AI and Ragas side by side. Both are tools in the Observability, Prompts & Evals category.

Quick Comparison

	Galileo AI	Ragas
Category	Observability, Prompts & Evals	Observability, Prompts & Evals
Pricing	Freemium	Open Source
Best For	AI teams who need to measure and improve the quality of their LLM outputs	Developers building RAG applications who need specialized evaluation metrics
Website	rungalileo.io	ragas.io
Key Features	LLM output quality evaluation Hallucination guardrails RAG evaluation metrics Data-centric AI debugging Automated error detection	RAG-specific evaluation framework Component-wise metrics for RAG Synthetic test data generation LLM-as-judge evaluators Open-source Python library
Use Cases	Monitoring LLM output quality Detecting and preventing hallucinations Evaluating RAG pipeline accuracy Debugging data quality issues Continuous quality assurance	Evaluating RAG pipeline quality end-to-end Measuring retrieval precision and recall Testing faithfulness and answer relevance Generating synthetic evaluation datasets Benchmarking RAG across configurations

When to Choose Galileo AI vs Ragas

Choose Galileo AI if you need

Monitoring LLM output quality
Detecting and preventing hallucinations
Evaluating RAG pipeline accuracy

Pricing: Freemium

Choose Ragas if you need

Evaluating RAG pipeline quality end-to-end
Measuring retrieval precision and recall
Testing faithfulness and answer relevance

Pricing: Open Source

About Galileo AI

Galileo is a data intelligence platform for AI that helps teams evaluate, debug, and improve LLM applications. It provides metrics for hallucination detection, context adherence, chunk quality, and response completeness. Galileo's guardrails can be deployed in production to catch quality issues in real-time.

View Galileo AI profile →Visit website

About Ragas

Ragas is an open-source evaluation framework specifically designed for RAG (Retrieval-Augmented Generation) pipelines. It provides metrics for context precision, context recall, faithfulness, and answer relevancy, helping teams measure and improve the quality of their RAG systems. Ragas has become the standard evaluation toolkit for teams building production RAG applications.

View Ragas profile →Visit website

What is Observability, Prompts & Evals?

Tools for monitoring LLM applications in production, managing and versioning prompts, and evaluating model outputs. Includes tracing, logging, cost tracking, prompt engineering platforms, automated evaluation frameworks, and human annotation workflows.

Browse all Observability, Prompts & Evals tools →