AI and platform teams
Understand which agents are running, what they own, and how execution behaves when clients disconnect or processes fail.
Deploy AI. Keep infrastructure control.
Designed for deployment patterns where enterprises want AI workloads to remain under their own infrastructure controls. Start with one real workload and a measurable boundary.
Security teams
Evaluate scoped authority, supported policy enforcement, execution evidence, and the remaining OS-level isolation requirements.
Your infrastructure, your pilot
Review private servers, VMs, cloud compute, and local environments with the JoyMux team. Confirm platform support, operational ownership, and integration requirements before production use.
01 / AGENT LAYER
Coding agentsAutonomous workersAI workflows
02 / JOYMUX RUNTIME
IdentityConcurrent sessionsWorkspace stateCompact contextDurable outputPolicy & grantsAction mediationTelemetryAnomaly detectionContainmentAudit & recovery
Resource and network enforcement require supported deployment controls.
03 / INFRASTRUCTURE
Operating systemProcesses & filesCompute & network
Conceptual architecture. Confirm platform and integration support for your environment.
EVIDENCE BEFORE CLAIMSTest it against
Test it against
a real workload.
Evaluate deployment effort, runtime behavior, and the controls that matter to your infrastructure. Agree on success criteria before the pilot begins.
CONTROL WHAT COMES NEXTAI agents are getting more authority.