Keywords AI
Ragas vs Sentry
Compare Ragas and Sentry side by side. Both are tools in the Observability, Prompts & Evals category.
Quick Comparison
| Category | Observability, Prompts & Evals | Observability, Prompts & Evals |
| Pricing | Open Source | — |
| Best For | Developers building RAG applications who need specialized evaluation metrics | — |
| Website | ragas.io | sentry.io |
| Key Features |
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| Use Cases |
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When to Choose Ragas vs Sentry
- Evaluating RAG pipeline quality end-to-end
- Measuring retrieval precision and recall
- Testing faithfulness and answer relevance
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.
About Sentry
Sentry provides runtime error monitoring and performance observability for AI applications. Its LLM monitoring capabilities track model calls, token usage, and latency alongside traditional error tracking. Sentry helps teams catch and debug issues in production AI pipelines with detailed stack traces and context.
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.
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