Arize Phoenix
Open-source AI observability platform for tracing, evaluation, and prompt management
About Arize Phoenix
Arize Phoenix is an open-source AI observability platform designed for experimentation, evaluation, and troubleshooting of LLM applications. It provides OpenTelemetry-based tracing, LLM evaluation benchmarks, dataset versioning, experiment tracking, and prompt management with version control. Phoenix integrates with major AI frameworks including LangChain, LlamaIndex, DSPy, and direct API calls to OpenAI, Anthropic, and other providers. The platform helps teams identify issues in their AI pipelines, compare model performance, and iterate on prompts — all without vendor lock-in thanks to its OpenTelemetry foundation. Available as open-source self-hosted or via Arize AX managed SaaS.
Pros & Cons
Pros
- Open-source with no vendor lock-in
- OpenTelemetry foundation ensures portability
- Comprehensive tracing and evaluation in one tool
- Integrates with all major LLM frameworks
- Active development and community
Cons
- Self-hosted version requires infrastructure management
- Hosted SaaS (AX) has limited free tier
- Enterprise pricing can be steep ($50K-100K/year)
Key Features
OpenTelemetry Tracing
Standards-based distributed tracing for LLM applications, ensuring portability across observability platforms
LLM Evaluation & Benchmarks
Built-in evaluation tools to benchmark model performance, measure accuracy, and compare outputs across different models
Prompt Management
Version-controlled prompt management with history tracking, comparison, and rollback capabilities
Dataset Versioning
Track and version datasets used for evaluation, enabling reproducible experiments and systematic improvement
Experiment Tracking
Track experiments across model versions, prompts, and configurations to identify optimal AI pipeline setups
Framework Integrations
Native integrations with LangChain, LlamaIndex, DSPy, OpenAI, Anthropic, and other major AI frameworks
Pricing
- Self-hosted deployment
- Unlimited spans
- Full tracing capabilities
- LLM evaluation
- Prompt management
- Community support
- Hosted SaaS
- 25K spans per month
- 7-day data retention
- Basic tracing
- Evaluation tools
- No credit card required
- 50K spans per month
- 15-day data retention
- Advanced tracing
- All evaluation features
- Priority support
- Team collaboration
- SOC 2 compliance
- HIPAA compliance
- Custom data retention
- Dedicated support
- SSO integration
- All Pro features
Best For
LLM Application Debugging
Trace and debug complex LLM pipelines to identify latency bottlenecks, hallucinations, and prompt failures
Model Performance Comparison
Evaluate and compare outputs across different LLM providers and model versions to select the best fit for your use case
Prompt Engineering Workflow
Iterate on prompts with version control, A/B testing, and systematic evaluation to improve AI application quality
AI Pipeline Monitoring
Monitor production AI systems with real-time tracing, alerting on quality degradation, and tracking usage patterns
Similar Tools
Visual Studio Code
Free, open-source code editor from Microsoft
Abacus.AI
The world's first AI super assistant for professionals and enterprises
Replicate
Run AI with an API
Cerebras
The world's fastest AI inference � 20x faster than GPU clouds
Chat2DB
AI-powered SQL client that turns natural language into database queries
Chroma
The open-source AI-native vector database for search and retrieval
Featured In
7 Best AI Benchmark & Model Comparison Tools for Choosing the Right LLM (2026)
Best for ML engineering teams who need to compare models within the context of their full AI pipeline — not just in isolation. The observability-first approach reveals performance differences that benchmarks miss.
7 Tools That Prevent AI Hallucinations in Customer-Facing Content (2026)
Best for enterprises that want to integrate AI content quality into their existing observability and DevOps practices
Ready to try Arize Phoenix?
Start using Arize Phoenix today and boost your productivity.
Visit Website