Domain representation
The objects, relationships, events, and language that describe your business.
Schemas · mappings · vocabulary
Domain Intelligence Layer design and deployment
Build and own the intelligence of your business.
IntelligenceOS defines and builds your Domain Intelligence Layer: the knowledge, decision logic, tools, authority, and operating experience that make AI useful in your business—and remain under your control as models change.
Built on Domain Intelligence, our engineering philosophy and strategy
Capability providersreplaceable ⇄
Hosted modelOpen-weight modelForecasting · optimisationSpecialist systems
Client-controlled boundaryYour Domain Intelligence Layer
01Domain representation
02Authoritative knowledge
03Decision logic and evaluations
04Tools and authority
05Institutional memory
06A learning process
ManifestAsset registryReconstruction package
Operational applications
Investigating exceptionsSupporting decisionsCoordinating workflowsExecuting approved actions
The strategic context
Preserve what makes your business distinct.
Access to capable AI is becoming more widespread. The intelligence specific to your business comes from something deeper: its domain knowledge, relationships, operating rules, expert judgment, and experience of what works.
We help you capture and structure that intelligence, put it to work, and create a foundation your organization can maintain and strengthen over time.
Increasingly available to everyone
- Capable foundation models
- General-purpose AI tools
- Reproducible software functions
Rent it · replace it
Specific to your business
- Domain knowledge
- Relationships
- Operating rules
- Expert judgment
- Experience of what works
Capture it · retain it · strengthen it
The Domain Intelligence Layer
A concrete asset inside your organization.
Your DIL connects how the business understands its domain, decides, acts, verifies results, and learns. These assets are defined, versioned, and connected to working applications. Together, they form a layer your team can inspect, use, and evolve.
Authoritative knowledge
The sources and current records your decisions depend on.
Source registry · provenance · freshness rules
Decision logic and evaluations
Your rules and the evidence for what good performance means.
Rules · decision tables · case sets
Tools and authority
The actions systems can perform and who controls them.
Typed tool contracts · roles · approvals
Institutional memory
Accepted precedents, corrections, and verified decision history.
Precedents · decision lineage
A learning process
A controlled way to turn operating experience into improved intelligence.
Feedback intake · promotion gates
What we build
Your domain, made operational.
We begin by defining the domain and the intelligence it needs. We then build the representations, rules, evaluations, tools, and controls around the decisions that matter.
Applications put that layer to work. Each application draws on the domain foundation and can contribute verified experience back to it.
01Investigating exceptions02Supporting decisions03Coordinating workflows04Executing approved actions
A synthetic example · shipment operations
Six artifacts from an illustrative logistics layer. Demonstration structures, not a client installation.
Domain map
How the domain is understood
The objects, relationships and vocabulary of shipment operations, with an explicit boundary: what this layer covers, and what it does not.
Manifest
One index for the whole layer
The manifest binds domain assets, policies, evaluations, tools, runtime and models to known versions, so any result can be traced to the configuration that produced it.
Asset registry
What exists, and who controls it
Every asset records its owner, rights, version, maintainer and dependencies — and what would be lost if a dependency disappeared.
Decision logic
Intelligence placed where it belongs
Current state comes from records, exact figures from deterministic tools, explanations from a model under review, permissions from policy — and the decision stays with people.
Evaluation case
Competence, defined by your reviewers
A protected case suite, independent of any one model, defines good performance and the failures that must never pass.
Operating result
Useful work — and something learned
One investigation: supported findings, an open question left open, an approved action verified in the destination system, and a correction returned to the layer.
What you retain
Retain your intelligence as technology changes.
The engagement establishes the assets your organization controls, the dependencies it uses, and how the layer can be maintained or reconstructed.
Your domain definitions, decision logic, evaluation assets, and agreed operating history remain inspectable and available under defined ownership and use arrangements. Model capability can come from different providers without making those providers the sole custodians of your accumulated intelligence.
We test agreed export, reconstruction, and model-change scenarios, documenting what transfers, what changes, and what it costs. The result is a practical continuity plan alongside the operating system.
Continuity, tested — not assumed
Agreed per engagement, with thresholds set before each test.
- 01ExportAssets and permitted history leave the deployment in documented formats
- 02ReconstructionThe layer rebuilds in a clean environment from its assets and instructions
- 03Model replacementThe same protected task suite runs on an alternate model adapter
- 04Authority continuityPermissions and approval rules hold through the migration
- 05Client stewardshipA named owner changes a rule and reruns acceptance
- 06Learning continuityAccepted corrections become versioned cases and rules
Accepted on two dimensions
A layer passes when it is useful and when it is yours.
Operational usefulness
- The agreed workflow performs useful work on representative cases
- Findings are supported by evidence or explicitly unresolved
- Calculations and actions are independently verified
- Measured against your baseline
Client control and continuity
- Rules, sources and versions are inspectable
- Assets export in documented formats
- The layer reconstructs from its package
- Behavior is retested on an alternate model
How we build
Define the layer. Build it. Put it to work.
- 01
Define your DIL
We map your domain, strategic knowledge, decisions, sources, authority, and dependencies. Together, we identify what the organization should retain and the first applications that can demonstrate value.
- 02
Build the intelligence assets
We structure the domain, connect authoritative sources, encode decision logic, define tool contracts, and create the evaluations and controls needed for the agreed scope.
- 03
Activate and verify
We deploy selected applications and evaluate their usefulness with your team. We also test the agreed ownership and continuity requirements of the layer behind them.
- 04
Retain and strengthen
We establish stewardship, documentation, and a controlled learning process. Verified outcomes and expert corrections become assets your organization can use to improve its DIL.
Across industries
A consistent philosophy. A DIL defined for your business.
We apply the same engineering strategy across industries while learning each organization’s domain on its own terms. The knowledge, rules, decision rights, and consequences are specific to the business.
The application is selected for its value to the domain. The DIL provides the foundation for extending that value into further decisions and workflows.
DIL assets to defineShipment and order relationships, milestones, carrier policies, accepted exception precedents
Shipment exception investigation
DIL assets to defineBatch and inspection relationships, quality rules, supplier knowledge, defect history
Quality deviation investigation
DIL assets to definePackage and contract relationships, procurement rules, milestone dependencies, issue history
Procurement issue triage
DIL assets to defineTransaction and ledger relationships, settlement rules, reconciliation logic, reviewed exceptions
Reconciliation discrepancies
DIL assets to defineCustomer and case relationships, SLA rules, routing authority, accepted resolution history
SLA breach investigation
Defined on its own terms
Every company’s domain, sources, decision logic, authority, language and failure costs are learned on their own terms. The machinery is reused; the intelligence is yours.
Discuss your domainDomain Intelligence
The philosophy behind IntelligenceOS.
Domain Intelligence organizes intelligence around the objects, knowledge, rules, decisions, actions, and feedback of a specific domain.
It guides where intelligence belongs—in current records, context, deterministic tools, model capability, policies, memory, or human judgment. It also determines what the organization should own and how that intelligence should survive changes in models and infrastructure.
IntelligenceOS applies this philosophy commercially by defining, building, deploying, and helping maintain the client’s DIL.
Where intelligence belongs
Current recordsWhat is true now, with provenance
ContextWhat the task needs to see
Deterministic toolsWhat must be calculated exactly
Model capabilityRented · replaceable
PoliciesWhat is permitted, and by whom
MemoryWhat has been learned and accepted
Human judgmentWhat people decide
Engagement
Begin with a defined domain.
A DIL assessment maps the intelligence assets you have, the dependencies and gaps that matter, and the decisions where a working layer can create value.
From there, we agree the initial domain boundary, assets, applications, and acceptance tests. Ongoing work can maintain freshness, improve performance, extend the domain, and strengthen the intelligence your organization retains.
DIL assessment and definition
One bounded domain: its strategic assets, decisions, dependencies, and activation priorities.
- DIL Definition
- Asset and liability inventory
- Ownership map
- Baseline
- Acceptance criteria and roadmap
DIL foundation and activation
The defined domain foundation, put to work through a first application for one team.
- Client DIL assets
- Manifest and asset registry
- Working application
- Operational and continuity tests
- Training and handover
DIL operation and evolution
Agreed support, asset freshness, reviewed learning, releases, and domain expansion.
- Operating and asset-health reports
- Client-approved improvements
- Continuity checks
- Incident handling
- Domain extension
Each stage has an asset deliverable and a usefulness test. New domains, applications, integrations or continuity drills are scoped separately.
FAQ
Questions teams ask first.
What will we have at the end of an engagement?
A DIL for the agreed domain: defined and versioned intelligence assets, accepted operational applications, an asset registry, documentation, and the agreed ownership and reconstruction package. The scope and dependencies are recorded explicitly.
Do we need our own foundation model?
Model choices follow the domain requirements and evaluation. Your organization may use hosted models, open-weight models, or existing specialist systems while retaining control of its domain assets.
How does the DIL protect our accumulated knowledge?
Through explicit ownership and access boundaries, confidentiality controls, versioned assets, documented dependencies, and tested continuity. Its usefulness and protection are maintained as knowledge, policies, and operations change.
Can our existing technology remain in place?
We assess how your current systems can supply or host parts of the layer. Architecture and integration choices follow your domain, access, and operating requirements.
How does the layer improve?
Verified outcomes, accepted corrections, and reviewed precedents become inputs to evaluations, rules, knowledge, and memory. Changes are assessed and approved before they alter operational behavior.
How do you measure value?
We measure agreed operational outcomes and the condition of the intelligence assets behind them. Evaluation includes quality, cost, and adoption, together with asset control, retained learning, and tested continuity.
Founded by
Ugo Chukwu — AI & Financial Systems Engineer. The engineering notes behind Domain Intelligence are published on Substack ↗; educational builds are on ethercess.com/work.
Discuss your domain
Define the intelligence your organization should own.
Bring us a business domain, the decisions it depends on, and the knowledge that makes it work. We will help define a concrete DIL and a practical path to building and using it.