Agentic Enterprise

Connect enterprise knowledge
to specialist agents at work

Design business applications, shared knowledge, verification, and approvals together. Specialist agents use the knowledge and tools their work requires and connect results to the next action.

Specialized agents.
Shared enterprise knowledge.

A coordinator connects specialist agents when a request spans domains. Agents use shared definitions and rules, with verification and approval controls governing business actions.

Specialized Agents. Shared Enterprise Knowledge.

Explore the architecture →
Agent-based Business AppsAnalysis · Options · Business actions
CoordinatorTask intent · Specialist coordination · Results
Opportunity AgentCustomer opportunities
Supply Planning AgentSupply options
Profitability AgentProfitability analysis
Shared Enterprise Knowledge Foundation
OntologyKnowledge GraphSemantic ViewPoliciesMetricsBusiness Rules

AI-ready Data ModelBusiness objects · Relationships · State · History · Source data

Decision / Control LoopObserve → Decide → Act → Verify → Learn

Define agents around expertise, responsibility, and permissions

Instead of concentrating every domain, tool, and permission in one giant agent, connect specialists through a coordinator where needed. Let business requirements and evaluations determine agent boundaries. A single agent or explicit workflow may be sufficient for simpler work.

Different decisions require different agents.

Profitability analysis and supply planning need different expertise, calculations, and change permissions. These differences can justify separate agents. Question types such as diagnosis, prediction, and simulation do not each require their own agent.

Align context, responsibility, and permissions

Context Boundary = Responsibility / Permission Boundary is a principle for aligning scope, not a security guarantee. Data services and tools must enforce actual permissions. A coordinator does not automatically inherit every agent’s authority.

What makes an agent an independent execution unit
Model
Reasoning and tool-use capability, latency, and cost.
System Prompt
Objectives, responsibilities, and business scope.
Tools
Queries, retrieval, calculation, and integrations.
Context
Current request, relevant history, and retrieved evidence.
Agent Loop
Further queries, execution, verification, and stopping.
Rules
Business conditions, stop criteria, and error handling.
Hooks
Pre- and post-execution checks, approvals, and records.
Sandbox
Isolation of code, files, network access, and credentials.

Manage state, tools, permissions, and evaluations per agent while reusing shared model services and runtime infrastructure.

Specialist responsibilities.
Shared business definitions.

Manage ontology, knowledge graph, semantic views, policies, metrics, and business rules as a shared foundation. Sharing definitions does not mean unrestricted access or a single physical store.

Ontology
Business concepts and relationships, such as customers, products, and orders.
Knowledge Graph
Connections among business objects, rules, documents, and evidence.
Semantic View
Mappings to data, query logic, and aggregation criteria.
Policies
Operating, approval, and access policies.
Metrics
Metric meanings, formulas, and scope.
Business Rules
Conditions, thresholds, precedence, and exceptions.
AI-ready data models and the knowledge layer

An AI-ready data model connects object identifiers, relationships, aggregation grain, state, history, and effective dates to source data. Available inventory needs an explicit location and time basis, with clear treatment of reservations, confirmed orders, and expected receipts.

The knowledge layer is the logical interface to business knowledge and data. Combine graph queries, retrieval, and semantic views as needed, checking permissions, sources, and versions. Link metric definitions to calculation implementations without duplicating them.

Observe → Decide → Act → Verify → Learn

Use validated tools for calculations and rules, and agents for interpretation and exploration. Automate pre-authorized actions and obtain approval where policy requires it. Feed outcomes and recurring exceptions into reviewed knowledge and operating criteria.