Govern the AI Workers you build, buy, or deploy — with customer-controlled identity, authority, human oversight, and evidence.

Agentic Enterprise Architecture

Design an agentic enterprise without letting AI workers outrun human accountability.

Scaled Agents connects enterprise architecture intent to customer-owned identity, bounded authority, Human Review, runtime decisions, evidence, and lifecycle control.

Create a Scaled Agent Explore the Control Plane

The Architecture Decision

Put AI-worker authority inside the enterprise control model.

Enterprise architecture already connects strategy, capabilities, applications, data, security, and technology. Agentic EA adds the control path for AI workers that can retrieve data, call tools, trigger workflows, or delegate work.

Architecture intent

Define the business purpose, accountable owner, data and system boundaries, risk, dependencies, and expected outcome.

Runtime authority

Decide the exact action an AI worker may take, under which policy and review conditions, for how long, and with what evidence.

Three Control Questions

Carry accountability from design intent to every consequential action.

Orchestration, models, data platforms, API gateways, service meshes, and observability remain execution inputs. They do not replace the customer-owned governance chain.

Who owns it?

The Agent Registry and Passport connect the AI worker to a human owner, purpose, risk tier, lifecycle state, and approved scope.

What may it do?

Purpose Binding and the Tool/API/Connector Registry define eligible actions, resources, data classes, destinations, and prohibited uses.

What permits this action?

A Toll Gate and Human Review can inform a short-lived Runtime Permit. The Action Broker is the controlled mediation path for the exact action when implemented and operated in the customer’s configured environment; evidence records preserve the result.

An active Passport establishes a current governance record. It does not authorize every action. Runtime authority remains action-specific, time-bounded, policy-bound, and revocable.

Reference Architecture

Place the control plane between architecture intent and AI-worker execution.

The architecture keeps customer strategy and enterprise standards connected to the authority, mediation, evidence, and lifecycle controls applied to AI-worker actions.

Shared Responsibility

Scaled Agents provides the control-plane platform. Customers govern their deployment and use.

The licensed platform provides structures for identity, authority, review, runtime decisions, evidence, and lifecycle management. Customer owners configure and operate those controls for their environment.

Scaled Agents

Provides the customer-managed platform, license, documentation, updates, and optional consultative services within the agreed scope.

Customer

Owns hosting, configuration, integrations, data, identities, policies, approvals, monitoring, custom changes, operations, and all decisions about deployment and use.

Accountable customer owners retain deployment, activation, legal, privacy, security, compliance, audit, risk acceptance, and production-operating decisions. Public architecture content does not make those decisions or grant AI-worker authority.

Next Step

Turn an AI-worker idea into an architecture-ready governance record.

Start with purpose, ownership, intended outcome, data, systems, autonomy, and risk—then connect the blueprint to the customer-owned control path.

Create a Scaled Agent Explore AI Worker Portfolio Management