The platform

A better runtime for AI to work in.

Persistent sessions, parallel execution, compact context, and shared workspace facts help agents keep useful work moving. Identity, policy, anomaly detection, and containment govern that same execution.

Discuss your workload

ONE SHARED EXECUTION FOUNDATION

Coding agentReview agentOperations agent

JoyMux runtime

Concurrent sessionsWorkspace factsCompact contextPersistent output

ObserveAttributeControlDetectContainRecover

Help agents work efficiently. Keep their execution accountable.

A BETTER ENVIRONMENT FOR AI

Less repeated work.
More useful execution.

Agents need more than a terminal. JoyMux gives them persistent execution, compact context, and shared workspace facts—so they spend less effort recovering state and repeating work.

Keep execution alive

Durable sessions separate the work from the client. Reconnect to the same execution history instead of rebuilding it from terminal output.

Persistent sessions · PTY workers · Event cursors

Run independent work in parallel

Concurrent process and PTY sessions keep input, output, and lifecycle state separate so independent jobs can progress together.

Concurrent sessions · Isolated streams · Structured state

Send the context that changed

Bounded delta views and explicit Context Capsules give agents compact catch-up information instead of repeatedly copying full histories.

Workspace deltas · Bounded context · Per-agent cursors

Avoid duplicate effort

Shared workspace facts and advisory warnings reveal overlapping edits, repeated tests, duplicate processes, and stale file state.

Workspace state · Handoff packets · Overlap warnings

Keep output moving

Disk-backed output and resumable reads let slow clients catch up without blocking process output or keeping the full history in memory.

Bounded memory · Durable output · Resumable reads

Give every harness the same foundation

Connect agents to a shared local execution protocol through hooks, CLI, or SDKs. Each harness keeps its own reasoning and planning.

Vendor-neutral runtime · Local APIs · Rust, Python & TypeScript

Where the efficiency comes from: less history to resend, fewer tasks to reconstruct, and independent work that can run concurrently. Measure the actual effect on your workload.

Explore the runtime

A boundary with a clear owner

JoyMux owns the execution session: process lifecycle, structured events, persistence, cancellation, and replay. Your agent framework continues to own reasoning and planning.

Authority is explicit

Scoped capability grants allow sensitive operations to pass through a broker. Authorization is evaluated before a supported action proceeds, and the decision leaves an audit record.

Detect anomalies. Contain the workload.

JoyMux detects abnormal runtime activity, attributes it to the affected agent, and supports containment of managed execution. Preserve the event trail for investigation and recovery.

Know the enforcement surface

Brokered operations and managed process launches can be mediated. Arbitrary child-process system calls and outbound sockets require additional operating-system isolation.

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.

Observe

See processes, resource use, execution events, and failure signals in one runtime context.

Structured events · Process visibility · Runtime telemetry

Attribute

Connect execution to an agent, workload, session, and authorization scope.

Agent identity · Session binding · Audit correlation

Control

Evaluate brokered actions against explicit policy before granting authority.

Scoped grants · Action mediation · Policy decisions

Detect

Detect abnormal resource use, repeated failures, and unexpected execution activity. Attribute the signal to the affected agent and workload.

Resource anomalies · Failure signals · Abnormal activity

Contain

Contain abnormal workloads by stopping managed execution, cleaning up its process group, and revoking brokered authority.

Cancellation · Process cleanup · Authority revocation

Recover

Reconnect to durable sessions and replay execution evidence after interruption.

Persistent events · Resumable reads · Recovery evidence

AN ATTRIBUTABLE EXECUTION RECORD

See the workload.
Understand the decision.

Explore a conceptual operator view. All agents and events below are illustrative, not live telemetry or a released dashboard claim.

Overview

Example workspace

Agent / workload	Host	CPU	Memory	State
build-agent-14backend-migration	enterprise-vm-03	94%	1.8 GB	Warning
review-agent-02pull-request-review	enterprise-vm-03	12%	640 MB	Healthy
ops-agent-07service-diagnostics	private-server-01	0%	256 MB	Contained

Each workload has an execution identity, resource observations, and an explicit state.

LATEST POLICY EVENTprivileged.invoke / Denied

Requested operation is outside the capability grant.

EVIDENCE BEFORE CLAIMS

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.

Discuss a 14-day technical pilot

CONTROL WHAT COMES NEXT

AI agents are getting more authority.
Your infrastructure needs more control.

Request a technical pilot Explore the architecture