ARArize Phoenix
Arize Phoenix — AI evaluation, observability, and safety platform for monitoring model quality, tracing prompt-response chains, running regression tests, and enforcing content safety policies.
Best for
- •Production AI systems that need continuous quality monitoring and alerting.
- •Teams shipping AI features that need pre-deploy evaluation pipelines.
Limitations
- •Eval metrics can give false confidence — always combine quantitative and qualitative review.
- •Tracing overhead can impact latency in high-throughput production systems.
Use carefully when
- •You're still prototyping and don't yet have production traffic to monitor.
Quickstart
- Instrument your LLM calls with the tracing SDK, then view traces in the dashboard.
- Set up eval datasets and run automated quality checks on each deployment.
Setup checklist
- • API key required: Yes
- • SDK quality: medium
- • Self-host difficulty: hard
Usage Notes
- • Validate model behavior on your own benchmark slices before rollout.
- • Pin version/provider routes for reproducible outputs.
- • Add logging + fallback routes for high-volume workloads.
Pricing (EUR)
Input / 1M
0,18 €
Output / 1M
0,45 €
Monthly
30 €
Capabilities
- evalHarnessYes
- promptTracingYes
- policyChecksYes
- regressionMonitoringYes
Benchmarks
overall Quality
64.2
reliability Index
71.9
benchmark Depth
67.5
Community reviews
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No reviews yet.
Samples
codeArize Phoenix demo
Eval harness config with prompt test cases and pass/fail thresholds.
Compliance
- License: proprietary
- Commercial use: allowed
Provenance
- Last verified: 15/4/2026
- Source: https://arize.com/phoenix