CL Compound Leverage Platform
Platform/Enterprise AI Team Architecture
AI Team Reference Architecture
Human Management
AI Team
Digital Employees
Skills
Orchestration
Execution Layer
Customer AI Control Plane
Enterprise Systems
Tools & Data

Enterprise AI Team Architecture

The AI Team architecture separates workforce design, execution, and customer governance so each can evolve independently.

Reference flow

Human direction → AI Team → Digital Employee → Skill → Orchestration → Execution → Customer AI Control Plane → Authorized systems and tools

The flow is logical rather than a requirement that every request pass through a separate software service. A capable runtime can perform several steps in one execution while preserving the boundaries needed for management and governance.

Logical layers

Human management

Managers and subject matter experts establish goals, provide organizational judgment, resolve ambiguity, review exceptions, and approve gated actions. See Human Management of AI Teams.

AI Team

The AI Team defines the business function and groups the Digital Employees required to perform it.

Digital Employees and skills

Digital Employees own jobs. Skills contain specialized methods, decision criteria, quality checks, and expected outputs. Keeping these separate prevents the persona or job definition from becoming an oversized prompt.

Orchestration

Orchestration coordinates workflow state, sequence, handoffs, validation, blocked work, and human approval gates.

Execution layer

The execution layer makes jobs and skills executable through plugins, agents, scheduled tasks, coding environments, or model-native mechanisms.

Customer AI Control Plane

The Customer AI Control Plane governs organizational context, identities, permissions, policies, data access, tool access, routing instructions, and audit boundaries for both humans and Digital Employees.

Enterprise systems and tools

Approved data stores, applications, APIs, browsers, search systems, connectors, MCP servers, and other tools provide the capabilities needed to perform work.

Model independence

A Digital Employee does not have to equal a separate model instance. One capable model may execute several logically distinct jobs while those jobs remain separate for ownership, evaluation, governance, auditability, and human management.

This is what allows the workforce definition to survive changes in model architecture.

See the architecture in practice

The AI Capture Team and AI Proposal Team show how these layers can be applied to complete business functions.