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.
Guardrails AI
Open-source framework for validating and correcting LLM outputs - a hub of validators (PII, toxicity, format, competitor mentions, hallucination) you compose around model calls.
| capability | Failproof AI | Guardrails AI |
|---|---|---|
| Built for | AI agents | LLM input/output |
| Agent-level tracing | Agent runtime, deeper | No |
| Autonomous failure finding | Automatic | No |
| Policy authoring | Yes | Validators (code) |
| Realtime policy enforcement | Yes, realtime | On LLM I/O |
| Enforcement scope | Agent actions | Model inputs & outputs |
| Content validators (PII, toxicity, format) | Some built-in | Yes |
| Deployment | Local, on-prem, cloud | Self-host (library) |
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 Guardrails AI when
- you need to validate or repair LLM text outputs
- you want composable content validators (PII, format, toxicity)
- your risk is the model output, not the agent actions
FAQ
Does Guardrails AI stop agent actions?
No - it validates and corrects LLM inputs and outputs (the text), not the agent tool calls. Failproof AI enforces policy on agent actions at the runtime and finds failures autonomously.
Guardrails AI vs Failproof AI?
Content validation vs agent-runtime governance. Guardrails AI checks model I/O against validators; Failproof AI traces the agent run, finds failure modes, and enforces policy on what the agent does.
Can I use both?
Yes - validate model output with Guardrails AI, govern agent behavior with Failproof AI.