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207 tools · 25 stacks

AI tools are all over the place. This is the full landscape — 207 tools across 17 categories, mapped and connected. Ready to narrow it down? Build your stack →

Team size

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Use case

Stage

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Stack Layers
What are you building and how is it defined?
How do you write and ship code?
How does your AI think and act?
Which models and infrastructure power it?
How do you build, observe, and extend it?
These tools competes with
DeepEval
vs
RAGAS

Choose DeepEval when…

  • •You want a pytest-style framework for LLM testing
  • •Unit-test-like evals for LLM outputs fit your workflow
  • •You need RAG-specific metrics like faithfulness and relevancy

Choose RAGAS when…

  • •You're evaluating a RAG pipeline specifically
  • •Context relevance and answer faithfulness are your key metrics
  • •You want an OSS eval framework focused on retrieval quality
Field
DeepEval
RAGAS
Category
Prompt & Eval
Prompt & Eval
Type
OSS
OSS
Free Tier
✓ Yes
✓ Yes
Plans
—
—
Stars
⭐ 5,500
⭐ 7,000
Health
●80 — Active
●55 — Slowing
Trajectory
— not enough data
— not enough data
Synced
today
today

DeepEval

Open-source evaluation framework with 14+ metrics including faithfulness, relevancy, and hallucination detection. Integrates with CI/CD.

RAGAS

Evaluates retrieval-augmented generation pipelines on faithfulness, answer relevancy, context precision, and recall.

DeepEval Website ↗GitHub ↗
RAGAS Website ↗GitHub ↗

Shared Connections (2)

LangfuseTruLens

Only DeepEval (5)

RAGASPromptFooOpenAI APIInspectGalileo

Only RAGAS (3)

LangChainLlamaIndexDeepEval
See full comparison in Explore →