Failproof AI
End-to-end reliability for AI agents. Traces every run at the agent runtime, finds where agents fail on its own, and lets you author and enforce a policy that stops the bad action in realtime - deployed on-prem or in the cloud.
Arize
ML-grade LLM observability. OpenTelemetry-native tracing, evals, and drift/embedding analysis (open-source Phoenix). Built to measure model quality.
| capability | Failproof AI | Arize |
|---|---|---|
| Built for | AI agents | LLM & ML |
| Agent-level tracing | Agent runtime, deeper | Model-level (OTel) |
| Autonomous failure finding | Automatic | Evals + drift, you configure |
| Policy authoring | Yes | No |
| Realtime policy enforcement | Yes, realtime | No |
| Drift & embedding analysis | No | Yes |
| Prompt management & eval datasets | No | Yes |
| Deployment | Local, on-prem, cloud | Phoenix self-host / cloud |
Choose Failproof AI when
- you run high-impact autonomous agents that take real actions
- a wrong action is costly or irreversible
- you need to stop failures at runtime, not just trace them
- you want an end-to-end reliability solution, on-prem or cloud
Choose Arize when
- you need ML-grade evals, drift, and embedding analysis
- you want OpenTelemetry-native, portable traces
- measuring model quality is your main goal
FAQ
Does Arize enforce policies at runtime?
No - Arize and Phoenix trace and evaluate, including online evals, but a score is a measurement, not an intervention. Failproof AI finds failures autonomously and enforces at the agent runtime, so a bad action is stopped, not just scored.
Arize vs Failproof AI?
Arize measures model quality (ML-grade evals, drift); Failproof AI delivers agent-runtime reliability, autonomous failure finding, and enforcement. Because Phoenix is OpenTelemetry-native, the two sit side by side cleanly.
Can I use both?
Yes - evaluate in Arize, enforce with Failproof AI.