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.
Datadog
LLM observability inside the Datadog APM platform - spans, token cost, and quality/security checks alongside your infra metrics and alerts.
| capability | Failproof AI | Datadog |
|---|---|---|
| Built for | AI agents | Apps + infra |
| Agent-level tracing | Agent runtime, deeper | APM / model-level |
| Autonomous failure finding | Automatic | Monitors & alerts you build |
| Policy authoring | Yes | No |
| Realtime policy enforcement | Yes, realtime | No (alert only) |
| Infra + LLM in one pane | No | Yes |
| Deployment | Local, on-prem, cloud | SaaS |
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 Datadog when
- you are standardized on Datadog for infra monitoring
- you want LLM spans next to your existing metrics and alerts
- one pane of glass matters more than intervention
FAQ
Does Datadog enforce agent policies?
No - it monitors and alerts. A dashboard pages a human; it does not stop the agent. Failproof AI finds failures autonomously and enforces at the runtime, in realtime.
Is monitoring enough for a production agent?
Monitoring suits the server era it was built for. Agents act faster than a human reads a dashboard and take irreversible actions - they need runtime enforcement.
Can I use both?
Yes - monitor in Datadog, enforce with Failproof AI.