Operational Model
The durable description of entities, relationships, state, history, evidence, decisions, policy, authority, workflows, and outcomes.
EntitiesRelationshipsStateHistoryEvidenceDecisionsPolicyAuthorityOutcomes
The Verimir Platform
The enterprise is the context. Verimir is the infrastructure.
Persistent context, governed evidence, replaceable models, controlled action, and continuous engineering form one enterprise intelligence environment.
Applications and experiences sit above operating intelligence, governed enterprise context, and infrastructure. Controlled action crosses an authority boundary to create an outcome. Observation returns along Layer 0 to challenge the system.
- 7ExperiencePeople · applications · agents
- 6 · 4 · 3Operating intelligenceDecision · runtime · replaceable models
- 5Governed enterprise contextEvidence · relationships · state · authority
- 2 · 1InfrastructureExecution · compute · storage · network
Authority boundary→OutcomeObservation returns ↺
Layer 0Purpose stays in the loop
Responsibility model · conceptual planes
Keep organizational meaning separate from the models and experiences that use it.
Experience, intelligence and control, and persistent enterprise meaning describe three conceptual responsibilities—not the literal architecture layers. A model can interpret evidence or recommend an action; it does not become the source of organizational truth or the authority that permits action.
Intelligence & Runtime Controls
Replaceable models and deterministic capabilities are assembled, constrained, evaluated, and permitted to use registered tools.
Context assemblyModelsRetrievalToolsRoutingEvaluationPolicy enforcement
Applications & Experience
People and systems work through domain experiences that use the shared model without becoming the system of record for every source.
PeopleAgentsWorkflowsDomain applicationsOperational interfaces
Architecture
Eight layers. One continuously challenged system.
Enterprise intelligence is not a model placed on top of enterprise data. Verimir separates infrastructure, execution, intelligence, organizational meaning, authority, and experience so each can evolve without collapsing the system into one technology.
Seven distinct operating layers rise from physical infrastructure through execution, replaceable models, intelligence runtime, a persistent enterprise operating model, controlled action, and applications. Layer 0, Purpose and System Design, forms a continuous governed circuit around the architecture. Controlled actions create real-world outcomes; observations return to Layer 0 as evidence so purpose and constraints can be revised.
- 7Applications & Experience
- 6Controlled Action
- 5Enterprise Operating Model
- 4Intelligence Runtime
- 3Models
- 2Execution Runtime
- 1Infrastructure
0
Purpose & System DesignAim · constraints · measurement · human role · system theory · learning
Purpose stays in the loop
Observation and outcomes challenge the assumptions the architecture was built against. Layer 0 continuously reshapes the system.Doctrine reference
Inspect the architecture.
The system view explains the relationship. Maturity labels come directly from the doctrine source. Expand a layer to inspect its exact doctrine and capabilities.
0Purpose & System Designoperating
The governed theory of purpose, boundaries, assumptions, and operating principles against which outcomes are evaluated.
What are we trying to improve—and how will we know?
Aim · Customer · Value · System · Variation · Measurement · Constraints · Human role
1Physical Infrastructureoperating
Customer-controlled compute, memory, storage, networking, datacenter, and edge environments.
Where does intelligence physically execute?
GPU · CPU · Memory · Storage · Networking · Datacenter · Edge
2Compute & Execution Runtimeresearch
Execution is optimized around the workload rather than assuming every model runs monolithically.
How should the governed workload execute?
Inference · Memory · Scheduling · Quantization · Selective execution · CPU/GPU distribution
3Models / Intelligence Enginesoperating
Open, specialized, statistical, deterministic, and frontier engines remain replaceable workloads.
Which replaceable capability fits the workload?
Open-weight · Specialized · Embeddings · Reranking · Statistical · Deterministic · Frontier
4Intelligence Runtimeoperating
The control plane assembles context, routes capability, applies policy, controls tools, and preserves evidence.
How is intelligence assembled, constrained, and evaluated?
Context · Routing · Retrieval · Tools · Policy · Workflow state · Evaluation
5Enterprise Operating Modelactive development
A versioned, governed theory of identity, meaning, evidence, state, authority, relationships, and history.
What does the organization currently know itself to be?
Evidence · Identity · Ontology · Semantics · Authority · Temporal state · Relationships · Computed facts
6Operating Intelligence & Controlled Actionactive development
Reasoning, decisions, approvals, actions, and outcomes remain inside explicit authority boundaries.
What should be concluded—and who may act?
Reason · Assess · Recommend · Approve · Execute · Audit · Learn
7Applications & Experienceoperating
Enterprise applications, domain workspaces, workflows, and customer experiences use the shared substrate.
Where do people and systems operate the intelligence?
Enterprise apps · Domain workspaces · Dashboards · Agent interfaces · Customer applications
Enterprise Intelligence Engineering
The platform is the architecture.
EIE is how it evolves.
Enterprise Intelligence Engineering is the implementation and operating discipline used to construct and continuously evolve Verimir environments.
It is not a one-time architecture phase or conventional IT consulting. The enterprise changes, the operating model is challenged, and the intelligence environment must change with it.
Enterprise Intelligence Engineering observes the operating environment, diagnoses what changed, models the problem, prioritizes work, engineers a response, measures outcomes, learns, and returns to observation.
Layer 0Purpose & System Design
↓Architecture↓Operation↓Outcome↓Observation↺Layer 0 does not end when implementation begins.
Purpose, constraints, assumptions, human roles, expected outcomes, and measurement remain active throughout the lifecycle.Verimir is the infrastructure.Enterprise Intelligence Engineering is the discipline used to build, operate, challenge, and improve it.
Operating principles
Durability is designed, governed, and maintained.
These principles keep enterprise intelligence from collapsing into one provider, one context window, or one application surface.
The platform architecture defines the responsibilities. The Operational Warehouse shows what persists underneath them.
Explore the Operational Warehouse →A useful first step
Start with one decision, workflow, or operating need that crosses systems.
Bring the systems, evidence, and people involved. We’ll identify a useful starting point for a governed Verimir environment.