Luthy gives teams runtime control over agent behavior in production—bounding execution cost, reducing monitoring overhead, and enabling safer deployment of longer-running multi-step workflows without manual supervision.
Try Luthy in Observer Mode free for 14 days to see where it would detect non-progress before enabling active intervention.
Non-progress detected
Optional orchestrator integrations can add richer runtime context
Luthy is building the runtime governance layer for production AI agents.
Luthy lets teams evaluate runtime protection safely before changing production behavior. Start in Observer Mode to see where Luthy would detect non-progress, estimate waste, and surface the runs most likely to benefit from intervention. Then enable active protection when you're ready.
Add Luthy on top of your existing Python agent runtime or orchestration layer.
See where loops, stalls, and wasteful continuation appear in live or test workloads.
Turn on active runtime protection once you've seen the value clearly.
Agents can keep acting without moving toward completion.
More steps and more tokens do not guarantee convergence.
Bad runs consume budget, latency, and operator attention before anyone notices.
Without runtime controls, systems drift outside intended operational limits.
Luthy observes agent behavior as it runs, detects low-signal or non-converging patterns, and enforces execution policies before failure compounds.
Track step-level behavior, progress signals, and execution flow
Identify loops, stalls, repetition, and low-value continuation
Apply policies to interrupt, constrain, or safely fail bad runs
Prevent recursive searching, repeated tool use, and low-signal continuation
Enforce runtime boundaries in workflows that affect business processes
Add execution governance where unattended runs need oversight and intervention
No. Luthy operates as an external runtime layer that observes execution behavior without altering model weights or requiring retraining.
Wrap your existing agent code with Luthy's protection layer. No infrastructure changes or model modifications required.
Luthy works with Python-based agent systems and any model API that your stack already calls.
Start free in Observer Mode, see where Luthy would detect non-progress, and enable active protection when the value is clear.