Arize Phoenix
Open-source LLM tracing and evaluation solution built on OpenTelemetry for RAG evaluation. Provides automated instrumentation which records the execution path of LLM requests through multiple steps.
About this tool
Overview
Arize Phoenix is an open-source observability and evaluation platform for LLM applications built on the OpenTelemetry standard. It provides comprehensive tracing and evaluation capabilities for RAG systems and AI agents.
Features
- OpenTelemetry-Based: Built on industry-standard observability framework
- Automated Instrumentation: Automatic tracing without code changes
- RAG Evaluation: Specialized metrics for RAG pipelines
- Trace Visualization: Detailed execution flow diagrams
- LLM Scorers: Multiple evaluation methods including LLM-as-judge
- Real-Time Monitoring: Production-ready observability
- Dataset Management: Track and version evaluation datasets
- Integration: Works with LangChain, LlamaIndex, and other frameworks
Evaluation Metrics
- Context relevance
- Answer correctness
- Hallucination detection
- Response quality
- Custom metrics support
Use Cases
- Debugging LLM applications
- RAG pipeline optimization
- Production monitoring
- Evaluation dataset curation
- Performance benchmarking
Integration
MLflow's third-party scorer framework supports Phoenix alongside RAGAS and TruLens. The platform is part of an ecosystem with 32M+ monthly PyPI downloads.
Pricing
Open-source under Apache 2.0 license. Arize also offers a commercial observability platform.
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Information
Websitephoenix.arize.com
PublishedMar 11, 2026
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