Failproof AI
End-to-end reliability for AI agents. Traces every run at the agent runtime, scores every finished session in the cloud with code checks, LLM judges and the eval set you already have (DeepEval, Ragas, promptfoo or your own), brought in as it is, 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.
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