Neptune.ai vs Arize Phoenix
Compare data AI Tools
0% Similar based on 0 shared tags
N
Neptune.ai
Experiment tracking, model registry, and metadata store that helps ML teams log, compare, and ship models with searchable runs and rich visualizations.
Pricing Free / $29 per month
Category data
Difficulty Beginner
Type Web App
Status Active
A
Arize Phoenix
Open source LLM tracing and evaluation that captures spans scores prompts and outputs, clusters failures and offers a hosted AX service with free and enterprise tiers.
Pricing Free, SaaS tiers by quote
Category data
Difficulty Beginner
Type Web App
Status Active
Feature Tags Comparison
Only in Neptune.ai
mlopsexperiment-trackingmodel-registrymetadatavisualization
Shared
None
Only in Arize Phoenix
llmobservabilitytracingevaluationopensourceotel
Key Features
Neptune.ai
- • Flexible logging: Track metrics params artifacts and images from any framework using light SDKs and callbacks
- • Search and compare: Slice runs by tags configs and scores to pick winners with evidence not memory
- • Custom dashboards: Build live charts tables and tiles to monitor long trainings and share status
- • Model registry: Store versions stages and approvals so releases are auditable and reversible
- • Collaboration: Organize workspaces projects and roles so large teams stay coordinated
- • Artifacts: Keep predictions checkpoints and plots alongside metrics for reproducibility
Arize Phoenix
- • Open source tracing and evaluation built on OpenTelemetry
- • Span capture for prompts tools model outputs and latencies
- • Clustering to reveal failure patterns across sessions
- • Built in evals for relevance hallucination and safety
- • Compare models prompts and guardrails with custom metrics
- • Self host or use hosted AX with expanded limits and support
Use Cases
Neptune.ai
- → Track baselines and ablations to defend decisions in reviews
- → Monitor long running experiments and intervene when metrics drift
- → Promote models through staged approvals with clear lineage
- → Share results with PMs and leads using links and dashboards
- → Attach artifacts so future teams can reproduce findings quickly
- → Automate comparisons in CI to block regressions before merge
Arize Phoenix
- → Trace and debug RAG pipelines across tools and models
- → Cluster bad answers to identify data or prompt gaps
- → Score outputs for relevance faithfulness and safety
- → Run A B tests on prompts with offline or online traffic
- → Add governance with retention access control and SLAs
- → Share findings with engineering and product via notebooks
Perfect For
Neptune.ai
ML engineers, researchers, data scientists, MLOps and platform teams who need reliable tracking and registries
Arize Phoenix
ml engineers data scientists and platform teams building LLM apps who need open source tracing evals and an optional hosted path as usage grows
Capabilities
Neptune.ai
SDKs and callbacks Intermediate
Runs at scale Intermediate
Versioned models Professional
Enterprise controls Professional
Arize Phoenix
Spans and Context Professional
Built in and Custom Intermediate
Clustering and Search Intermediate
Hosted AX Basic
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