AIchitect
StacksGraphBuilderSimulateCompareGenomeActivityPulse
235 tools · 33 stacks

AI tools are all over the place. This is the full landscape — 247 tools across 21 categories, mapped and connected. Ready to narrow it down? Build your stack →

Team size

Budget

Use case

Stage

Cluster

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?
Browse all categories →
These tools integrates with
LangChain
vs
RAGAS

Choose LangChain when…

  • •You want a broad, flexible LLM orchestration toolkit
  • •You need integrations with many tools and data sources
  • •You're prototyping or exploring LLM app patterns

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
LangChain
RAGAS
Category
Pipelines & RAG
Prompt & Eval
Type
OSS
OSS
Free Tier
✓ Yes
✓ Yes
Plans
—
—
Stars
⭐ 93,000
⭐ 7,000
Health
●100 — Active
●70 — Active
Trajectory
— not enough data
— not enough data
Synced
today
today

LangChain

Most widely used framework for building LLM applications. Chains, agents, RAG pipelines, and deep integrations with 300+ tools.

RAGAS

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

LangChain Website ↗GitHub ↗
RAGAS Website ↗GitHub ↗

Shared Connections (2)

LlamaIndexLangfuse

Only LangChain (31)

OpenHandsCrewAIAutoGenLangGraphSemantic KernelLangSmithQdrantChroma

Only RAGAS (3)

LangChainDeepEvalTruLens
See full comparison in Explore →