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Arize

AI Observability · Evaluated by Moneda AI

Teams running production AI systems that need model and LLM observability

CategoryAI Observability

FromCustom pricing

Best forTeams running production AI systems that need model and LLM observability

Wins1 of 5

What it’s for

  • Model performance and drift monitoring
  • Tracing and evaluation workflows
  • LLM and prediction observability dashboards

Pricing

  • Custom pricing

Job fit, data protection, and security

Sourced entity notes for buyers who need more than a feature list. Claims link to vendor docs — re-check before regulated or privileged use.

Deploymentcloud · self-host · air-gap

Data protection

Training on customer data
Customer data is not used for training Arize models.Sourcechecked 28 Aug 2026
Retention
Configurable retention policies for traces.Sourcechecked 28 Aug 2026
Residency
Supports EU data residency.Sourcechecked 28 Aug 2026

Security

Certifications / controlsSOC 2 Type II · ISO 27001checked 28 Aug 2026

Would not choose if

  • Teams solely seeking lightweight batch logging without a dedicated ML platform team.
  • Organizations needing LLM evaluation strictly built from the ground up, rather than adapted from general ML monitoring.
  • Buyers who require a simple, fully managed cloud-only solution without any self-hosting or air-gapped deployment options.

Where Arize appears — and how it did

Arize helps ML and AI teams monitor production quality, diagnose failures, and improve model behavior with evaluation and tracing tools.