Autonomous health monitoring and self-healing for AI agent fleets. Arcflow catches failures, triggers remediation, and predicts cascades — before they cost you.
Built for humans who click alerts and run playbooks. Agents don't click. They fail silently and cascade.
LangSmith, Helicone, Arize — great for debugging one agent. Useless when you have 200 agents running simultaneously.
You hired autonomous agents to eliminate human work. Now you have humans monitoring them 24/7. That's not autonomy — that's outsourcing the on-call.
Continuously evaluates every agent in your fleet: response latency, error rates, budget consumption, hallucination signals, tool call patterns. Detects degradation before it becomes failure.
Define conditions. Arcflow acts. When an agent exceeds latency thresholds, burns too much budget, or enters a loop — it intervenes automatically. Restart, retry, route around, kill.
Agents depend on each other. When one starts failing, the others often follow. Arcflow maps your fleet topology and predicts which failures will cascade — so you can isolate before it spreads.
Cross-agent pattern recognition. If one class of agent starts failing in one context but not others — Arcflow learns why and shares the fix. Your fleet gets smarter over time.
One SDK integration. Add the Arcflow client to any agent framework — LangGraph, AutoGen, CrewAI, custom. No instrumentation changes needed.
Set thresholds in plain YAML: latency limits, budget caps, retry budgets, escalation rules. Arcflow enforces them autonomously.
Live dashboard shows your entire fleet's health. Interventions are logged and auditable. When Arcflow acts, you see why and can override anytime.
Agents that fail unsupervised are liability, not automation. Arcflow is the layer that makes autonomous operations actually autonomous — not just "runs without a human clicking buttons" but "handles its own failures."