A² (Agentic Architecture)™
The Architecture Behind 100% Automation
The only framework synthesizing TOGAF, DDD, BPMN/DMN, and AI governance into a unified agentic operating system. Built from first principles. Validated in enterprise deployments.
Proprietary Framework
The Seven Separations™
Seven axioms of agent-native enterprise architecture. Violating any one of them is the root cause of automation project failure.
Different reasoning types require different frameworks. Mixing cognitive modes creates brittle, unmaintainable agents that fail at scale.
Core Architecture
Three-Layer Execution Model
The single most differentiating concept in agentic architecture. Mixing these three layers is the primary cause of brittle, unmaintainable automation.
Key principle: LLM agents ONLY handle genuine cognitive tasks. Everything deterministic → DMN. Everything orchestrated → BPMN.
Orchestration
BPMN Process Flow
WHO does what, IN WHAT ORDER
Business Process Model and Notation governs orchestration — which agent or human performs which step, and in what sequence. Fully auditable. Fully deterministic.
Deterministic Rules
DMN Decision Tables
DETERMINISTIC logic: eligibility, thresholds, rules
Decision Model and Notation handles all rule-based logic — eligibility checks, approval thresholds, compliance conditions. Auditable, explainable, and changeable without redeploying agents.
Cognitive Tasks
Agent Cognition
WHERE LLMs add genuine value
Large language model agents handle only genuine cognitive tasks — interpretation, synthesis, and judgment. LLMs are expensive, probabilistic, and hard to audit. They should never touch deterministic logic.
Proprietary Pattern
Control Gate™ Pattern
A 4-stage verification pipeline applied at every agent boundary. External verification is mandatory — agents never govern themselves.
Agents NEVER govern themselves. External verification is mandatory.
Schema Validation
Output structure verified against typed contracts. Malformed outputs are rejected before downstream systems see them.
Confidence Check
Probabilistic confidence scores are measured against business-defined thresholds. Low-confidence outputs route to human review.
KG Consistency
Outputs are cross-referenced against the Knowledge Graph for factual consistency. Hallucinations are caught before they propagate.
Audit Logging
Every agent decision, output, and escalation is written to an immutable audit log. Full trace for NIST, ISO, and EU AI Act compliance.
Architecture Layers
11-Layer Enterprise Architecture
Four new agentic layers built on top of seven proven enterprise layers. Strict downward dependencies prevent circular coupling.
Governance-First Architecture
NIST · ISO · EU AI Act — Baked In
Governance is not an afterthought in Agentic OS. It is baked into every Control Gate™, every bounded context, and every ADC™ cycle.
Governance is a competitive advantage, not a compliance burden.
NIST AI RMF
US StandardMAP
Identify AI risks, stakeholders, and system context before deployment.
MEASURE
Quantify risks with metrics, testing, and red-teaming protocols.
MANAGE
Prioritize and treat identified risks through Control Gates™ and monitoring.
ISO/IEC 42001 + 23894
InternationalAI Management System
Structured management system for AI risks across the organization.
Risk Integration
AI risk management integrated into enterprise risk frameworks.
Continual Improvement
Audit, review, and uplift cycles aligned with ADC™ EVOLVE phase.
EU AI Act
Fully Applicable Aug 2026Risk Classification
Classify all AI systems by risk level (Unacceptable, High, Limited, Minimal).
Transparency Obligations
Disclose AI use, provide explanations, maintain interaction logs.
Human Oversight
Mandate human control at all high-risk decision boundaries.
Domain-Driven Design
7 Bounded Contexts
Each bounded context is independently governable, deployable, and evolvable. Anti-corruption layers at every boundary prevent domain bleed.
Strategy & Portfolio
Investment priorities, capability mapping, Wardley evolution tracking.
Customer / Stakeholder
Customer identity, interaction history, preference models, CRM integration.
Knowledge & Content
Knowledge graph, document corpus, vector embeddings, taxonomy management.
Workflow & Decisions
BPMN process definitions, DMN decision tables, workflow state machines.
Agent Operations
Agent lifecycle, skill registry, execution queues, load balancing.
Risk & Compliance
Risk taxonomy, audit logs, compliance policies, Control Gate™ records.
Platform & Observability
Infrastructure telemetry, fitness functions, cost optimization, alerting.
Ready to see the architecture in action?
Book a discovery session and we'll walk through how A² Agentic OS applies to your specific domain, stack, and automation targets.