Arize Phoenix Alternative · Self-hosted · Open Core

AgentLens vs Arize Phoenix
Production-grade observability without the notebook lock-in.

Phoenix is a great notebook-first ML observability tool from Arize. AgentLens is built for production-tier teams who need compliance, SLA, and a self-hosted deployment that runs as a real service — not a notebook.

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Quick Comparison

Feature-by-feature

Capability AgentLens Arize Phoenix
Production deployment (not notebook)✓ Docker + cron + persistent SQLiteNotebook-first design
Self-hosted (free OSS)✓ open-core, BSL 1.1✓
Multi-step agent waterfalls✓ trace_agent + spansVia OpenInference traces
Automatic quality + hallucination flags✓ zero configEval framework, manual setup
Air-gap mode (single env var)✓ tcpdump-verifiedManual config
EU-hosted managed cloud✓ FrankfurtArize cloud is US
DPA + audit log + retention✓ Scale plan built-inArize AX paid contract
Plan-tier feature gating (server-side)✓ Free / Starter / Team / Scale / EnterpriseArize AX is enterprise-tier only
Framework-agnostic SDK✓ any PythonOpenInference standard

Based on public Arize Phoenix pricing as of May 2026. Verify at https://phoenix.arize.com/.

When to choose what

Honest recommendation

Choose Arize Phoenix if…

  • Your team works primarily in notebooks (data science workflow)
  • You're already on the Arize AX platform for ML observability
  • You need OpenInference / OpenTelemetry-native instrumentation
  • You want broader ML coverage (CV + tabular + LLM)

Choose AgentLens if…

  • You're shipping LLM features in a production service (not notebooks)
  • You need compliance workflows out of the box (DPA, audit, retention)
  • Your buyer wants air-gap mode that's verifiable
  • You want a clear paid tier ladder (€299–5,000/mo) instead of enterprise-sales-only
Migration

Switching from Arize Phoenix takes ~30 minutes

Both tools share a similar mental model. The SDK surface is different but migration is mechanical.

# Before (Phoenix in notebook)
import phoenix as px
session = px.launch_app()
 
# After (AgentLens)
import agentlens
agentlens.init("http://localhost:8000/ingest")
agentlens.patch_openai() # or patch_anthropic()
FAQ

Common questions

Is AgentLens compatible with OpenInference/OpenTelemetry?

Native compatibility is on the roadmap. For now, AgentLens uses its own SDK; OpenInference adapter is planned for Q3 2026.

Why pick AgentLens over Phoenix?

Production deployment posture (Docker + persistent SQLite + cron-driven evals + alerts) plus compliance workflows + plan-tier ladder. Phoenix is notebook-first; AgentLens is service-first.

Can I use AgentLens for ML models beyond LLMs?

Currently focused on LLMs and agents. CV/tabular monitoring is not on the immediate roadmap.

Ready to own your LLM data?

15-minute migration call. We'll map your Arize Phoenix setup to AgentLens and get you running.

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