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.
Braintrust
Eval-first platform: datasets, scorers, experiments, and regression testing in CI. Built to measure and improve output quality before you ship.
| capability | Failproof AI | Braintrust |
|---|---|---|
| Built for | AI agents | LLM evals |
| Lifecycle stage | Runtime (production) | Pre-ship (CI) |
| Autonomous failure finding | Automatic | Offline scorers |
| Policy authoring | Yes | No |
| Realtime policy enforcement | Yes, realtime | No |
| Eval datasets & CI regression | No | Yes |
| Deployment | Local, on-prem, cloud | Cloud / hybrid |
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 Braintrust when
- you want a rigorous offline eval workflow
- you need CI regression testing on prompts and outputs
- your focus is pre-ship quality, not runtime governance
FAQ
Does Braintrust enforce anything at runtime?
Not in the sense of stopping an action - it evaluates and logs. Failproof AI finds failures autonomously and enforces at the agent runtime once agents are live.
Can a good eval score prevent a bad agent action?
No - a score describes past outputs; it cannot stop the next live action. Failproof AI does, at the runtime.
Can I use both?
Yes - gate quality in Braintrust, enforce behavior with Failproof AI.
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