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Arize Phoenix

Open-source observability and evaluation tooling for LLM applications, traces, datasets, and experiments.

by Arize AI·added 2026-04-27·
HarnessCLI
Review first review before installing

Open the source and read safety notes before installing.

Citation facts

Source-backed facts for citing this resource, derived directly from the registry — also available as plain text for AI assistants.

Source URLs
https://arize.com/docs/phoenix, https://github.com/Arize-ai/phoenix, https://arize.com/phoenix/
Brand
Arize Phoenix
Brand domain
arize.com
Brand asset source
brandfetch
Author
Arize AI
Claim status
unclaimed
Last verified
2026-04-27

Decision playbook

Review trust signals before you adopt

Signals are present but mixed. Use the checklist below to confirm the source and operational safety for your environment.

Required checks are still incomplete. Finish source and safety verification before adopting this resource.

Compare context
Selected

0

Current score

58

Baseline

Delta

No baseline selected

No major trust-signal divergence detected in the current selection.

Source and provenance checks

Complete

Confirm ownership and provenance before trusting install instructions.

  • Source link availableRequired

    Open the canonical repository and verify ownership.

    Done
  • Source provenance statusRequired

    Marked as source-backed.

    Done
  • Metadata reviewed

    Registry metadata indicates a reviewed listing.

    Done

Safety and privacy checks

Required checks missing

Validate risk disclosures before installation or API wiring.

  • Safety notes presentRequired

    No safety notes listed.

    Pending
  • Privacy notes presentRequired

    No privacy notes listed.

    Pending
  • Trust level risk gateRequired

    Trust level does not block evaluation.

    Done

Package and install checks

Needs review

Check package metadata and artifact integrity signals.

  • Install payload available

    Install or copy payload is available for review.

    Done
  • Package verification flag

    No package verification flag provided.

    Pending
  • Checksum metadata

    No checksum provided for downloaded artifact.

    Pending

Compare-driven decision checks

Needs review

Use compare context to validate trade-offs before adoption.

  • Compare tray has multiple entries

    Add at least one more entry to compare trust differences.

    Pending
  • Baseline comparison available

    No baseline peer selected yet.

    Pending
  • Diverging trust signals identified

    No major trust-signal divergence found.

    Pending

Setup at a glance

Copy & paste

Copy-ready — paste the snippet to get started.

Install command

Not provided

Config snippet

Not provided

Copy snippet

Provided

Prerequisites

None

Platforms

1 listed

Install type

Copy & paste

Adoption plan

Balanced adoption plan

Current risk score 44/100. Use staged verification before broader rollout.

Risk 44
Adoption blockers
  • Safety notes are missing.
  • Privacy notes are missing.

Pre-adoption checks

Validate source and review signals before any execution.

  • Confirm source provenanceRequired

    Source URL/provenance metadata is present.

    Done
  • Confirm metadata review state

    Listing has review metadata.

    Done
  • Verify install payload

    Install/config payload exists and can be inspected.

    Done

Security checks

Confirm safety, privacy, and package integrity signals.

  • Review safety notesRequired

    Safety notes missing; review source code paths before execution.

    Pending
  • Review privacy notesRequired

    Privacy notes missing; inspect network/data behavior manually.

    Pending
  • Verify package integrity metadata

    No package verification/checksum metadata.

    Pending

Rollout

Adopt in controlled steps based on the selected plan.

  • Run in isolated sandbox firstRequired

    Use a constrained sandbox and observe behavior across multiple tasks.

    Pending
  • Roll out graduallyRequired

    Roll out to a small cohort before wider usage.

    Pending
  • Set monitoring and fallback

    Define rollback path and monitor errors after adoption.

    Pending

Evidence readiness

Evidence readiness matrix · balanced

Missing required evidence: Safety notes. Risk score 36.

Risk 36

Source provenance

Present

Source repository/provenance is listed.

Required in this preset

Metadata review

Present

Review metadata is present.

Required in this preset

Safety notes

Missing

Safety notes are missing.

Required in this preset

Privacy notes

Missing

Privacy notes are missing.

Optional in this preset

Package integrity

Missing

Package integrity metadata is missing.

Optional in this preset

Install payload

Present

Install payload is available.

Required in this preset

Required gaps: Safety notes

Decision timeline

Decision timeline · balanced

Blocking gaps: Review safety notes. Risk 32.

Risk 32

triage

Confirm source provenanceRequired

Source/provenance metadata is available.

Done

triage

Check metadata review statusRequired

Review metadata is available.

Done

verify

Review safety notesRequired

Safety notes are missing.

Pending

verify

Review privacy notes

Privacy notes are missing.

Pending

verify

Validate package integrity metadata

Package integrity metadata is missing.

Pending

rollout

Verify install payload and commandsRequired

Install payload is available.

Done

Blockers: Review safety notes

Schema details

Install type
copy
Troubleshooting
No
Source repository stats
Scope
Source repo
Skill and platform metadata
Retrieval sources
https://arize.com/docs/phoenixhttps://opentelemetry.io/https://docs.smith.langchain.com/https://docs.helicone.ai/https://www.braintrust.dev/docs
Tool listing metadata
Pricing
open-source
Disclosure
editorial
Application category
DeveloperApplication
Operating system
Web, Self-hosted
Full copyable content
## Key capabilities

- **Tracing** — captures LLM/agent spans (prompts, tool calls, retrievals) using OpenTelemetry, so traces are portable across instrumented frameworks.
- **Evaluation** — run LLM-as-a-judge and heuristic evals over traces and datasets to score relevance, hallucination, and task success.
- **Datasets & experiments** — curate examples from production traces and compare prompt/model versions side by side.
- **Self-hosted or local** — run Phoenix locally or in your own infrastructure, keeping trace data in your environment.

## How Phoenix compares

Phoenix sits in the LLM observability/evaluation space alongside several tools also in this directory. Key differences:

| Tool | Type | Self-hostable | Notable for |
| --- | --- | --- | --- |
| **Arize Phoenix** | Open-source observability + evals | Yes | OpenTelemetry-based tracing that runs locally |
| **LangSmith** | Proprietary observability + evals | Enterprise tier | Deep LangChain / LangGraph integration |
| **Helicone** | Observability via a request-logging proxy | Yes | One-line integration that captures requests |
| **Braintrust** | Proprietary evals + experimentation | SaaS | Eval-first experimentation workflow |

Choose Phoenix when you want open-source, OpenTelemetry-native tracing and evaluation you can run locally; pair it with Helicone if you also need request-level logging.

## Editorial notes

Phoenix is useful for teams that want open-source tracing and evaluation workflows around agent and LLM behavior.

## Disclosure

Editorial listing. No paid placement or affiliate link is used.

About this resource

Key capabilities

  • Tracing — captures LLM/agent spans (prompts, tool calls, retrievals) using OpenTelemetry, so traces are portable across instrumented frameworks.
  • Evaluation — run LLM-as-a-judge and heuristic evals over traces and datasets to score relevance, hallucination, and task success.
  • Datasets & experiments — curate examples from production traces and compare prompt/model versions side by side.
  • Self-hosted or local — run Phoenix locally or in your own infrastructure, keeping trace data in your environment.

How Phoenix compares

Phoenix sits in the LLM observability/evaluation space alongside several tools also in this directory. Key differences:

Tool Type Self-hostable Notable for
Arize Phoenix Open-source observability + evals Yes OpenTelemetry-based tracing that runs locally
LangSmith Proprietary observability + evals Enterprise tier Deep LangChain / LangGraph integration
Helicone Observability via a request-logging proxy Yes One-line integration that captures requests
Braintrust Proprietary evals + experimentation SaaS Eval-first experimentation workflow

Choose Phoenix when you want open-source, OpenTelemetry-native tracing and evaluation you can run locally; pair it with Helicone if you also need request-level logging.

Editorial notes

Phoenix is useful for teams that want open-source tracing and evaluation workflows around agent and LLM behavior.

Disclosure

Editorial listing. No paid placement or affiliate link is used.

Source citations

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How it compares

Arize Phoenix side by side with 3 alternatives on trust, install, platform support, and disclosed safety notes — all from reviewed registry metadata.

Field

Open-source observability and evaluation tooling for LLM applications, traces, datasets, and experiments.

Open dossier

Observability, evaluation, tracing, and testing platform for LLM applications and agent workflows.

Open dossier

Open-source LLM observability platform for logging, metrics, cost tracking, feedback, and gateway workflows.

Open dossier

Open-source LLM engineering platform for tracing, prompt management, evaluation, metrics, and observability.

Open dossier
Next steps
Trust
Review statusReviewedMaintainer reviewedReviewedMaintainer reviewedReviewedMaintainer reviewedReviewedMaintainer reviewed
Package trustPackage not verifiedPackage not verifiedPackage not verifiedPackage not verified
Source provenanceSource-backedSource-backedSource-backedSource-backed
Submitter
Install riskReview firstReview firstReview firstReview first
Notes Safety · Privacy · Safety · Privacy Safety · Privacy Safety · Privacy
BrandArize Phoenix logoArize PhoenixLangSmith logoLangSmithHelicone logoHeliconeLangfuse logoLangfuse
Categorytoolstoolstoolstools
Sourcesource-backedsource-backedsource-backedsource-backed
AuthorArize AILangChainHeliconeLangfuse
Added2026-04-272026-04-272026-04-272026-04-27
Platforms
CLI
CLI
CLI
CLI
Source repo
Safety notes— missing— missing— missing— missing
Privacy notes— missingLangSmith receives traces of your LLM and agent runs — prompts, outputs, tool calls, and metadata — sent to LangSmith's cloud (or your self-hosted instance); review what trace data leaves your environment and keep secrets out of logged inputs.When used as a proxy, Helicone sits in the request path and logs your LLM prompts, responses, and metadata (Helicone cloud or your self-hosted instance); review what request data is captured, keep secrets out of logged payloads, or use the self-hosted/async logging options.Langfuse receives traces of your LLM/agent runs — prompts, outputs, and metadata — sent to Langfuse Cloud or your self-hosted instance; review what trace data leaves your environment and keep secrets out of logged inputs.
Prerequisites— none listed— none listed— none listed— none listed
Install
Config
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