Purpose
Define the decision, system boundary, fidelity requirement, update cadence, horizon, and accountable owner.
MUST CLOSE BEFORE ADVANCEMENTCAPABILITIES / DIGITAL TWIN
CAP–T07EVIDENCE-BOUND SYSTEM ARCHITECTURE
Model what is observed. Expose what is assumed.
KAIA digital twins are living decision models that bind physical, cyber, organizational, financial, social, and policy state to provenance, time, uncertainty, causality, constraints, authority, and outcome measurement.
ARCHITECTURE STATEOBLIGATIONS TYPED
- 01Purpose
- 02State
- 03Dynamics
- 04Use
A useful twin is not a photorealistic mirror. It is a controlled hypothesis about a system: what exists, how it changes, which evidence updates it, which interventions are admissible, and where the model must abstain.
DECISION CONTRACT
Bound the capability before listing the features.
Every workflow begins with an explicit decision contract that determines system behavior and acceptance evidence.
State
Separate observation, estimate, inferred relation, latent variable, constraint, and unknown.
MUST CLOSE BEFORE ADVANCEMENTDynamics
Declare mechanisms, equations, rules, agent behavior, exogenous shocks, and calibration evidence.
MUST CLOSE BEFORE ADVANCEMENTUse
Bound scenarios, optimization, intervention, authority, validation, monitoring, and retirement.
MUST CLOSE BEFORE ADVANCEMENTINTERACTIVE RUNTIME SPECIFICATION
Input, transformation, output, control, and failure—at every layer.
Select a layer to inspect how the architecture transforms evidence and which failure must trigger abstention.
T01 / State model
Represent multiple truths without collapsing them.
Entity, topology, geometry, event, resource, organization, policy, and environmental state retain effective time, knowledge time, source, confidence, and competing versions.
INPUTObservations · events · configuration
→TRANSFORMATIONState model
→OUTPUTBitemporal twin state
- ACTIVE CONTROL
- Provenance + reconciliation
- FAILURE TO PREVENT
- Stale mirror presented as current reality
OPERATING PATTERNS
One capability. Different decisions and failure boundaries.
These patterns are notional architectural scopes—not claims about customers, deployments, or outcomes.
Mission rehearsal
Test plans, logistics, communications, threat, terrain, and authority across adversarial branches.
- DECISION
- Which plan is robust to the most consequential uncertainties?
- GOVERNANCE BOUNDARY
- Simulation does not establish real-world mission success
Supply network twin
Model suppliers, capacity, inventory, routes, demand, dependencies, shocks, and recovery.
- DECISION
- Where should intervention preserve service and optionality?
- GOVERNANCE BOUNDARY
- Source freshness and causal limits remain visible
Financial and operational stress twin
Connect obligations, liquidity, services, counterparties, infrastructure, controls, and response choices.
- DECISION
- Which feasible response meets limits under stress?
- GOVERNANCE BOUNDARY
- Not a forecast, valuation, or trading instruction
Policy and resource simulation
Compare allocation or procedure alternatives across outcomes, distributional effects, constraints, and uncertainty.
- DECISION
- Which trade-offs require accountable human judgment?
- GOVERNANCE BOUNDARY
- Model output cannot replace lawful authority or consultation
GEO-SEMANTIC TWIN
Interrogate location, relationship, state, and authority on the same surface.
The 2D/3D scene uses explanatory notional data; locations do not represent customers, facilities, or real operations.
KAIA / GEO-SEMANTIC TWINExplanatory operating topology
PUBLIC-SECTOR PATTERNMission ContinuityMODELED
NOTIONAL · EXPLANATORY · NO CUSTOMER/OPERATIONAL DATAASSURANCE EVIDENCE LEDGER
A claim is only as strong as the boundary of its evidence.
Each assurance domain requires an explicit owner, method, scope, result, exception, and residual risk.
Fidelity contract
Purpose, scale, resolution, update rate, variables, accuracy, and permissible decisions are defined.
EXPECTED EVIDENCETwin charter · variable dictionary · thresholds
Calibration + validation
Parameters and mechanisms are compared with representative observation and held-out conditions.
EXPECTED EVIDENCECalibration record · residuals · validation report
Uncertainty + sensitivity
Aleatory and epistemic uncertainty, dependencies, sensitivities, and scenario coverage are explicit.
EXPECTED EVIDENCEUncertainty budget · sensitivity analysis
Lifecycle control
Version, access, change, drift, incident, rollback, supersession, and retirement are governed.
EXPECTED EVIDENCEConfiguration record · monitoring · retirement decision
The system must not advance to action before reality passes type-checking.
Change the controls to inspect how evidence, authority, and environment stress alter admissibility.
ILLUSTRATIVE INTEGRITY INDEX77
CONDITIONAL REVIEW
- Thresholds satisfied; authorized human decision remains required.
This interaction is deterministic and explanatory.
NEXT DECISION
Define the decision fidelity—not the visual fidelity.
Bring the system boundary, state variables, dynamics, data, scenarios, unacceptable divergence, authority, and validation plan.