Arize is a mature ML monitoring platform with drift detection and model performance tracking. It's ML observability, not agent governance — no proven step-level re-execution, no pre-run policy enforcement, no regulatory compliance mappings.
| Capability | Arize AI | Runback | Note |
|---|---|---|---|
| Model performance and drift monitoring | ✓ | partial | Arize speciality. Runback detects behavioural drift in agent outputs (from the Scale plan), but doesn't monitor ML model performance |
| Embeddings and vector analysis | ✓ | ✗ | Arize speciality |
| LLM trace capture | ✓ | ✓ | |
| Re-execute any agent step from captured inputs | partial | ✓ | Phoenix Span Replay re-runs a captured LLM span with edits, and 'Agent Replay' appears in a 2026 self-hosted release note — mechanism and granularity undocumented; no evidence of bisection or deterministic re-execution of tool state |
| Live policy enforcement — block before it runs | ✗ | ✓ | Arize's guardrails correct or retry a response after generation, not intercept a tool call before it runs. Runback decides each tool call server-side, from its TypeScript and Python SDKs (not yet Go or an MCP proxy), against the policy version assigned to the agent; each assignment fails closed or open during an outage (closed by default for agents declared critical, once the SDK has fetched its policy bundle), and decisions are recorded and sealed — those the SDK makes on its own once Runback answers again |
| CI release gate for model upgrades | partial | ✓ | Markets 'evaluation gating' — block or require review on an eval regression; less proven than Runback's history-simulated gate |
| Signed, tamper-evident audit export | ✗ | ✓ | Monitoring metrics are aggregated for dashboards, not sealed as individual signed records |
| Self-host, data in your perimeter | ✓ | ✓ | Phoenix is free to self-host under the Elastic License 2.0 — source-available, not open source, the same standard Runback applies to itself; Arize AX also offers on-prem enterprise deployment |
| Regulatory mappings (EU AI Act · CPS 230 · NIST) | ✗ | ✓ |
It's ML observability, not agent governance — no proven step-level re-execution, no pre-run policy enforcement, no regulatory compliance mappings. Most teams use both — Arize AI for what it's already good at, Runback for deterministic incident replay and the signed record.
Source: Arize AI's public documentation, https://docs.arize.com/arize, read 15 September 2026. Products change: report an error to legal@runback.dev and we will correct it. Names and trade marks belong to their owners; Runback is not affiliated with, endorsed or sponsored by any of them.
No signup. Walk the scripted failing demo run step by step and see what the model was given.