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.
Langfuse
Open-source LLM observability. Built for LLM calls - tracing, evals, datasets, and prompt management to measure and debug model output. Self-hostable.
| capability | Failproof AI | Langfuse |
|---|---|---|
| Built for | AI agents | LLM calls |
| Agent-level tracing | Agent runtime, deeper | Model-level |
| Autonomous failure finding | Automatic | You dig through traces |
| Policy authoring | Yes | No |
| Realtime policy enforcement | Yes, realtime | No |
| Prompt management & eval datasets | No | Yes |
| Deployment | Local, on-prem, cloud | 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 Langfuse when
- you need prompt management and eval dataset creation
- you measure LLM output quality more than agent actions
- you want a mature eval and annotation workflow
FAQ
Is Failproof AI a Langfuse alternative?
For end-to-end agent reliability - agent-level tracing, autonomous failure finding, and policy enforcement - yes. For prompt management and eval datasets, Langfuse is the specialist; many teams run both.
Langfuse traces LLM calls - how is Failproof AI tracing different?
Failproof AI is built for agents: it traces the whole run at the agent runtime - tool calls, actions, decisions - and finds the failure modes on its own, rather than leaving you to dig through model-call traces.
Do I have to migrate off Langfuse?
No. Failproof AI installs alongside and deploys on-prem or in the cloud.