Respan
LLM tracing, evals, and gateway
Phoenix — Observability, Prompts & Evals Platform
Founded 2023|Berkeley, California|Part of Arize AI (~50-100 employees)|Open Source
What is Phoenix?
Phoenix is the open-source observability and evaluation platform built by Arize AI for LLM and agent applications. It is OpenTelemetry-native, which means traces written through Phoenix can flow into any OTel-compatible backend in addition to Phoenix's own UI. The platform includes built-in evaluators for hallucination detection, retrieval relevance, and QA correctness, plus dataset management and prompt playground features. Phoenix can be deployed via Docker for self-hosting or used in Arize's managed cloud. The open-source core makes it attractive to teams that want to inspect and customize the observability layer, while the integration with the full Arize platform provides an upgrade path for organizations that need enterprise features like RBAC, SSO, and SLA-backed support.
Key features
Core capabilities this platform advertises.
- OpenTelemetry-based LLM and agent tracing
- Built-in evaluators for hallucination and relevance
- Dataset and experiment management
- Prompt playgrounds and versioning
- Self-hosted Docker deployment or Arize cloud
Strengths and tradeoffs
What this tool does well, and the limitations to keep in mind.
Pros
- Open-source with active development by Arize
- OpenTelemetry-native (no proprietary trace format lock-in)
- Strong evaluator library out of the box
- Both self-hosted and managed cloud options available
- Upgrade path to full Arize enterprise platform
Cons
- Smaller community than Langfuse for open-source-first teams
- Cloud version's enterprise pricing is contact-sales only
- UI and feature set tilt toward ML engineers more than application developers
Common use cases
Engineering teams building agent and RAG systems who want OpenTelemetry-native observability with both self-hosted and managed options
- OpenTelemetry-native LLM observability
- Hallucination detection for RAG
- Experiment tracking and golden-set evaluation
- Prompt iteration and comparison
- Self-hosted tracing for compliance-sensitive teams
Best Phoenix alternatives & competitors
Top companies in Observability, Prompts & Evals you can use instead of Phoenix.
LangSmith
Trace visualization for LLM chains
Weights & Biases
ML experiment tracking
MLflow
OpenTelemetry-native tracing
Langfuse
Open-source LLM observability
Arize AI
ML observability with LLM support
Helicone
Traceloop
OpenTelemetry
Datadog LLM
LLM monitoring within Datadog platform
HoneyHive
Prompt management
Braintrust
Real-time LLM logging and tracing
Promptfoo
Patronus AI
Automated LLM evaluation platform
Humanloop
Portkey
Sentry
DeepEval
Ragas
RAG-specific evaluation framework
LangWatch
Multi-turn agent simulation testing
Galileo AI
LLM output quality evaluation
PromptLayer
Confident AI
DeepEval open-source evaluation framework
Maxim AI
Distributed tracing for LLM and agent apps
Opik
Agenta
Future AGI
Multimodal evaluation (text, image, audio, video)
Lunary
Parea AI
Moda
Hallucination detection
Chamber
ML infrastructure automation
Ashr
Multi-modal synthetic testing
Sentrial
Agent failure root cause analysis
Athina AI
Compare Phoenix
Side-by-side comparisons with other tools in this category.
Best integrations for Phoenix
Companies from adjacent layers in the AI stack that work well with Phoenix.
