FleetPulse gives autonomous fleets a nervous system — real-time health monitoring, anomaly detection, and self-healing orchestration that keeps your agents running when you'd otherwise be debugging blind.
You deploy a fleet of AI agents. They run 24/7. And then something breaks at 3am and you have no idea which agent failed, why, or how to fix it before it cascades.
Traditional monitoring was built for humans at desks. AI agents don't file reports — you have to instrument every workflow manually just to see what's running.
One agent fails silently. Others depend on its output. The failure compounds across your workflow before anyone notices — and by then you've lost hours of data.
When a human goes down at work, someone notices. When an agent fails, everything that depended on it keeps running against stale data until someone manually intervenes.
FleetPulse instruments your agent fleet end-to-end — from heartbeat to resolution — so your fleet can detect, diagnose, and recover from failures without a human in the loop.
Lightweight SDK drops into any agent. Telemetry streams in real-time — latency, error rates, dependency health, resource consumption — without slowing your agents down.
Anomaly detection runs continuously on fleet telemetry. Baseline establish, threshold breach triggers — before a human would have noticed something was wrong.
FleetPulse orchestrates self-healing — restart stalled agents, reroute workloads around failures, alert only on edge cases that actually need human attention.
Most monitoring tells you something broke. FleetPulse tells you what broke, why, and initiates the fix — then learns from every incident to prevent the next one.
Autonomous agents deserve the same operational rigor we give human infrastructure. Real-time visibility, intelligent remediation, and the confidence that your fleet is running — even when you're asleep.