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RagaAI Catalyst
Python SDK for Agent AI Observability, Monitoring and Evaluation Framework. Includes features like agent, llm and tools tracing, debugging multi-agentic system, self-hosted dashboard and advanced analytics with timeline and execution graph view
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01
At a glance.
A compact read before the deeper capability notes and official setup links.
02
Core features.
Feature cards focus on what the tool helps users do, not generated setup commands.
RagaAI Catalyst is a comprehensive platform designed to enhance the management and optimization of LLM projects.
It offers a wide range of features, including project management, dataset management, evaluation management, trace management, prompt management, synthetic data generation, and guardrail management.
Create and manage projects using RagaAI Catalyst:
Manage datasets efficiently for your projects:
For more detailed information on Dataset Management, including CSV schema handling and advanced usage, please refer to the Dataset Management documentation.
Create and manage metric evaluation of your RAG application:
For more detailed information on Trace Management, please refer to the Trace Management documentation.
The Agentic Tracing module provides comprehensive monitoring and analysis capabilities for AI agent systems.
04
Agent / Skill / MCP / Workflow fit.
This panel keeps technical format separate from the user-facing AI category.
05
Official setup path.
Generated install snippets are intentionally not mirrored here because they drift. The page links to source-owned setup docs instead.
06
Evidence and adoption notes.
These notes help a user decide whether to investigate the official project further.
Source repository last pushed at 2026-02-11T14:43:33Z.
Generated from source metadata; confirm operational details in the official project before adopting it.
Review the upstream license, maintenance activity, and issue history before using it in production.
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