Keywords AI

Confident AI vs Ragas

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

Quick Comparison

	Confident AI	Ragas
Category	Observability, Prompts & Evals	Observability, Prompts & Evals
Pricing	Open Source	Open Source
Best For	Developers who want to add automated LLM evaluation testing to their CI/CD pipeline	Developers building RAG applications who need specialized evaluation metrics
Website	confident-ai.com	ragas.io
Key Features	DeepEval open-source evaluation framework 14+ evaluation metrics Benchmarking suite Pytest integration Conversational evaluation support	RAG-specific evaluation framework Component-wise metrics for RAG Synthetic test data generation LLM-as-judge evaluators Open-source Python library
Use Cases	Unit testing LLM applications Automated evaluation in CI/CD pipelines Benchmarking across model versions RAG evaluation with custom metrics Regression testing for prompts	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 Confident AI vs Ragas

Choose Confident AI if you need

Unit testing LLM applications
Automated evaluation in CI/CD pipelines
Benchmarking across model versions

Pricing: Open Source

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 Confident AI

Confident AI develops DeepEval, the most popular open-source LLM evaluation framework. DeepEval provides 14+ evaluation metrics including faithfulness, answer relevancy, contextual recall, and hallucination detection. The Confident AI platform adds collaboration features, regression testing, and continuous evaluation in CI/CD pipelines.

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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.

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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 →