AIPay AgentOS

Run enterprise Agents inside governed business workflows

Connect knowledge, data, tools, and systems while governing Agent identity, permissions, model use, cost, approvals, and execution history.

Global models

Local models

Governance control plane
Identity
Cost & value
Security audit
Employees
Business systems
AgentOS

A working Agent is not yet a production operating model

Excessive permissions

Agents often rely on shared credentials or overly broad permissions.

Opaque execution

Model, tool, and data actions lack a consistent execution record.

Drifting cost

Loops and complex workflows can consume model and system resources without clear limits.

Treat each Agent as a governed digital work unit

AgentOS provides runtime, connectivity, and governance foundations with configurable human approval for high-risk steps.

Agent identity

Assign an identity, owner, and operating scope to every Agent.

Tool connectivity

Connect knowledge, databases, APIs, and business systems.

Approvals and exceptions

Add human approval, timeout, and exception handling to critical actions.

Runtime governance

Track model use, cost, tool calls, and execution outcomes.

Typical deliverables

  • Agent use-case and boundary design
  • Connector and runtime configuration
  • Permission, budget, and approval policy
  • Pilot, monitoring, and optimization plan

Who this is for

  • Enterprises integrating AI into business workflows
  • Critical processes requiring human approval
  • Teams with Agent prototypes but no operating governance

Next step

Bring your operating context into a concrete architecture discussion

Discuss AgentOS architecture