Keywords AI

Braintrust vs Ragas

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

Quick Comparison

	Braintrust	Ragas
Category	Observability, Prompts & Evals	Observability, Prompts & Evals
Pricing	Freemium	Open Source
Best For	AI teams who need a unified platform for logging, evaluating, and improving LLM applications	Developers building RAG applications who need specialized evaluation metrics
Website	braintrust.dev	ragas.io
Key Features	Real-time LLM logging and tracing Built-in evaluation framework Prompt playground Dataset management Human review workflows	RAG-specific evaluation framework Component-wise metrics for RAG Synthetic test data generation LLM-as-judge evaluators Open-source Python library
Use Cases	Iterating on prompts with real production data Running evaluations across model versions Building golden datasets from production traffic Human-in-the-loop review of LLM outputs Cost and latency optimization	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 Braintrust vs Ragas

Choose Braintrust if you need

Iterating on prompts with real production data
Running evaluations across model versions
Building golden datasets from production traffic

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 Braintrust

Braintrust is an end-to-end AI product platform trusted by companies like Notion, Stripe, and Vercel. It combines logging, evaluation datasets, prompt management, and an AI proxy with automatic caching and fallback. Braintrust's evaluation framework helps teams measure quality across prompt iterations with customizable scoring functions.

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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 →