What is Arize Phoenix?
Phoenix provides OpenTelemetry-based instrumentation for LLM applications, AI-powered evaluation of model outputs and retrieval quality, and systematic prompt management with versioning. It supports both self-hosted and cloud deployment and integrates with major LLM frameworks and development tools.
What Arize Phoenix does
The capabilities that matter for llm observability, normalised so it lines up with every alternative. “-” means we haven't confirmed it, not that it's missing.
- Architecture model
- Open source self hosted
- Token cost and latency waterfall charts
- ✓
- Opentelemetry openllmetry native export support
- ✓
- Prompt playground and in dashboard replay
- ✓
- Multi step agentic workflow distributed tracing
- ✓
- User feedback score API for thumbs up down tags
- -
- Pii redaction and prompt content masking
- -
- Production ab testing of system prompts
- ✓
- Automated anomaly detection for rate limits
- -
- Native integration with langchain and llamaindex
- ✓
- SOC2 type ii
- -
- Mit or apache permissive oss license
- -
- Pricing model
- Free open source
Platform & deployment
Independently observed- Cloud / SaaS
- Self-hosted
Integrations (8)
Independently observed- LlamaIndex
- OpenAI
- Anthropic
- AWS Bedrock
- Vertex AI
- Claude Code
- Cursor
- OpenLLMetry
Security & compliance
Known vulnerabilities: 0 (0 in the last 12 months) sourcea count reflects scale & disclosure, not quality
Arize Phoenix alternatives
Other llm observability we track, ranked by the same independent score.
- TraceloopContinuous evaluation and monitoring platform for LLM applications that catches quality issues before productionmedium · 54%
- LunaryMonitor and optimize AI applications in productionhigh · 75%
- Weights & Biases WeaveMonitor and analyze AI agents and multi-turn systems in production environmentslow · 9%
- AgentOpsPlatform for monitoring, debugging, and deploying production-ready AI agentsmedium · 55%
- OpikMonitoring and evaluation tools for AI agent applicationslow · 36%
The Vioscale score: one lens on the evidence
Not user reviews and not a paid placement: a confidence-weighted blend of the independent signals below (adoption, activity, security posture, and more), which you can sort and re-weight yourself. Vendors can correct their listing but can never move their rank, and stars are weighted low as a vanity metric. It is one way to read the evidence for Arize Phoenix, not the verdict.
| Signal | Score | Weight | Contribution | Evidence |
|---|---|---|---|---|
| Capabilities | 81 | 0.08 | 6.8 | ✓ |
| Development activity | 63 | 0.09 | 5.9 | ✓ |
| Integrations | 27 | 0.09 | 2.6 | ✓ |
| Stars | 76 | 0.03 | 2.0 | ✓ |
| Price level | 0 | 0.05 | 0.0 | - |
| Reliability | 0 | 0.07 | 0.0 | - |
| Dependent projects | 0 | 0.06 | 0.0 | ✓ |
| Release cadence | 0 | 0.05 | 0.0 | - |
| Security posture | 0 | 0.07 | 0.0 | - |
| Package downloads | 0 | 0.14 | 0.0 | - |
| Security score | 0 | 0.04 | 0.0 | - |
| Pricing transparency | 0 | 0.08 | 0.0 | - |
| Developer Q&A activity | 0 | 0.06 | 0.0 | - |
Computed . Re-weight it by intent, or see the full method.
All data & sourcesshow ↓
Every value we hold, with its source, retrieval date, and confidence. This is the evidence behind the score: don't trust it, verify it.
Activity
| Attribute | Value | Evidence |
|---|---|---|
| Commits last 30d | 100 | mediumsource · 2026-08-26 · 65% |
Adoption
Features
| Attribute | Value | Evidence |
|---|---|---|
| Capabilities | Pricing model: free_open_source · Architecture model: open_source_self_hosted · Production ab testing of system prompts: Yes · Token cost and latency waterfall charts: Yes · Prompt playground and in dashboard replay: Yes · Multi step agentic workflow distributed tracing: Yes | mediumsource · 2026-08-21 · 60% |
Integrations
| Attribute | Value | Evidence |
|---|---|---|
| Count | 8 | mediumsource · 2026-08-21 · 60% |
Language
| Attribute | Value | Evidence |
|---|---|---|
| Primary | Python | highsource · 2026-08-26 · 90% |
Pricing
| Attribute | Value | Evidence |
|---|---|---|
| Model | commercial | mediumsource · 2026-08-26 · 60% |
Release
| Attribute | Value | Evidence |
|---|---|---|
| History | 20 items | mediumsource · 2026-08-26 · 70% |
Security
| Attribute | Value | Evidence |
|---|---|---|
| Vulnerabilities | Count: 0 · Source: https://advisories.ecosyste.ms/api/v1/advisories?ecosystem=pypi&package_name=arize-phoenix-client&per_page=100 · Last 12m: 0 | highsource · 2026-08-26 · 90% |