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Secure AI Infrastructure

Rytuz AI — Secure Machine Access

Infrastructure for AI systems to operate a user's local or authorized remote machines in a controlled, bounded and observable way.

MCPAuthorized execution
RegistryMachine lifecycle
AuditObservable actions
RecoveryBounded recovery

Bounded execution

AI access is not a single command; it is a chain of permission, lifecycle, audit and recovery.

01MCP

Execution surface

02Registry

Machine registry + lifecycle

03Bounded

Bounded operation

04Audit

Observable record

05Recovery

Controlled recovery

The challenge

Enable an AI agent to do real work without giving it unrestricted machine access, while making permission, audit, recovery and lifecycle boundaries explicit.

What we built

An execution platform is being developed around MCP-compatible access, machine registry/lifecycle, audit and recovery components.

Verified capabilities

  • MCP-compatible execution surface
  • Machine registry and lifecycle
  • Audit records
  • Recovery mechanisms
  • Bounded and controlled automation

Repository evidence

src/oryx_access/mcp_local.pysrc/oryx_access/machine_registry.pysrc/oryx_access/machine_lifecycle.pysrc/oryx_access/audit.pysrc/oryx_access/recovery.py

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