Overview

Rating

10.0 / 10

Rating

Best For

Developers building RAG applications who need specialized evaluation metrics

Best For

Engineering and product teams running AI agents and LLM apps in production

Product Summary

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.

Product Summary

Respan is LLM observability built into an AI router: nested traces for every agent run, evals on live production traffic, and a click from any score to its trace.

Starting Price

Open Source

Starting Price

Free Trial

Yes

Free Version

Yes

Website

ragas.io

Website

respan.ai

Key features

Core capabilities each platform advertises.

Ragas

RAG-specific evaluation framework
Component-wise metrics for RAG
Synthetic test data generation
LLM-as-judge evaluators
Open-source Python library

Respan

Nested traces for every LLM call, tool run, and agent turn
Threads for multi-turn sessions
Online evals on live production traffic
LLM-judge, code, and human evaluators
Datasets from production logs and experiments at scale
Monitors with Slack, email, and webhook alerts
Prompt versioning and deployment without code changes

Strengths and tradeoffs

What each tool does well, and the limitations to keep in mind.

Ragas

Pros

Specialized focus on RAG evaluation with metrics specifically designed for retrieval systems
Open-source framework providing transparency and community-driven development
Strong industry endorsement from OpenAI, LangChain, and LlamaIndex
Y Combinator backing providing credibility and potential for growth
Easy integration with popular frameworks like LangChain and LlamaIndex

Cons

Very small team of 3 employees may limit support and feature development
Limited to RAG evaluation, not a comprehensive observability solution
Minimal funding ($500K) compared to competitors may impact long-term sustainability
Lack of clear commercial pricing model for enterprise features

Respan

Pros

Every score links to the trace that produced it
Evals run on live production traffic, not only on test sets
Built into the router, so there's no separate gateway to integrate
Monitors alert the moment a metric breaches
Unlimited seats on the free plan

Cons

Ragas or Respan — which should you choose?

Choose Ragas if you wantChoose if you want

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

Choose Respan if you wantChoose if you want

Debugging agent failures down to the step that broke
Catching quality regressions before users report them
Turning production failures into test datasets
Testing a prompt or model change against real cases before shipping
Attributing LLM cost to each end customer

Compare Ragas and Respan on your own traffic

10KFree traces/mo

1,000+Models

5 minSetup

Respan lets you trace LLM and agent calls across any model or framework, A/B test prompts on production traffic, and route requests across 1,000+ models through one gateway.

Try Respan free

Ragas vs Respan (2026)

Overview

Key features

Strengths and tradeoffs

Ragas or Respan — which should you choose?

Compare Ragas and Respan on your own traffic

Other popular comparisons