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MonitoringFreemiumOpen Source
RAGAAI
Open-source observability, monitoring and evaluation for agent AI
Apache-2.0
ABOUT
Agentic AI applications are notoriously hard to debug and evaluate — multi-step agent loops, tool calls, and LLM interactions produce complex execution graphs that are invisible to traditional monitoring tools. RagaAI Catalyst solves this by providing comprehensive tracing of agents, LLMs, and tools in a unified dashboard with timeline and execution graph views, plus built-in evaluation metrics for RAG quality, agent performance, and guardrail effectiveness — making it possible to observe, debug, and measure AI application quality in production.
INSTALL
pip install ragaai-catalystINTEGRATION GUIDE
1. Trace and debug multi-agent systems with execution graph views showing agent decisions, tool calls, and LLM interactions
2. Monitor LLM application performance in production with latency, token usage, and error rate dashboards
3. Evaluate RAG pipeline quality with metrics for retrieval relevance, context utilization, and response faithfulness
4. Set up guardrails and monitor their effectiveness with built-in safety evaluation metrics
5. Debug agentic workflows by replaying traces with detailed timeline views of each step in the execution
TAGS
monitoringobservabilityllmagentsevaluationtracingdebugging