KAROS is an autonomous runtime infrastructure network for AI agents, programmable workflows, realtime execution, and machine-native systems — coordinating compute and settling execution economically, in realtime.
AI systems will require autonomous execution, programmable coordination, realtime settlement, and distributed workflow orchestration. Today's stack was built for humans clicking buttons — not for machines executing each other's intent at scale.
KAROS is the substrate for that shift: a network where execution is the primitive, not the page.
Modern AI systems can automate tasks, but the rails underneath them are broken into pieces.
KAROS turns execution into programmable, settle-able infrastructure.
A persistent execution substrate where machine-native systems run without human orchestration.
Workflows fire, branch, and resolve in realtime — measured, observable, and economically settled.
Compute is routed dynamically to the optimal provider by latency, cost, and reliability — every call.
Independent runtime nodes coordinate as one fabric — no central scheduler, no single point of failure.
Every unit of execution is metered and settled automatically through Idle-powered economic rails.
Any API becomes a programmable, composable execution layer that agents can call and compose.
Idle Protocol powers the settlement and monetization infrastructure behind KAROS. Execution becomes measurable, workflows become programmable, and infrastructure providers earn — automatically.
The coordination asset of the runtime network — staked by operators, spent on execution, and used to govern the protocol.
View tokenomicsBranding, website, documentation, Idle integration.
Workflow registry, execution routing, infrastructure onboarding.
Distributed runtime orchestration and realtime workflow management.
Autonomous execution markets and machine-native infrastructure economies.
The next generation of AI systems will run autonomously. KAROS provides the runtime infrastructure powering that transition.