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Confident AI vs Ragas (2026)

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Overview

Rating
10.0 / 10
Rating
10.0 / 10
Best For
Developers who run LLM evals in CI with DeepEval and want a hosted platform for tracing, datasets, and online evals
Best For
Developers building RAG applications who need specialized evaluation metrics
Product Summary

Confident AI is the LLM evaluation and observability platform from the creators of DeepEval. Compare its pricing, features, pros and cons, and alternatives.

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.

Starting Price
$0
Starting Price
Open Source
Free Trial
No
Free Trial
No
Free Version
Yes
Free Version
No
Website

Key features

Core capabilities each platform advertises.

Confident AIConfident AI
  • DeepEval open-source evaluation framework
  • LLM-as-a-judge metrics
  • CI/CD regression testing
  • LLM tracing and online evals
RagasRagas
  • RAG-specific evaluation framework
  • Component-wise metrics for RAG
  • Synthetic test data generation
  • LLM-as-judge evaluators
  • Open-source Python library

Strengths and tradeoffs

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

Confident AIConfident AI

Pros

  • Open-source DeepEval runs locally without the platform
  • Per-organization pricing with unlimited seats from Starter up
  • Tracing, evals, and annotation in one workspace
  • Red teaming and governance in the same platform on Enterprise

Cons

  • No built-in gateway, so routing needs a separate tool
  • Free plan limited to two seats, one project, and five test runs a week
  • Online evals and annotation queues start at $200/month
  • On-prem deployment and HIPAA are Enterprise only
RagasRagas

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

Confident AI or Ragas — which should you choose?

Choose Confident AI if you want

  • Unit testing LLM applications
  • Automated evaluation in CI/CD pipelines
  • RAG evaluation with custom metrics
  • Regression testing for prompts

Choose Ragas 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

Compare Confident AI and Ragas on your own traffic

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1,000+Models
5 minSetup

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