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AII

Assurance Intelligence Index

Quantifying Assurance, Integrity, and Trust Across the ECO Number Network

1. Assurance Architecture Overview

The ZAYAZ Assurance Intelligence Index (AII) provides a quantitative measure of data quality, process integrity, assurance maturity, and ecosystem trust across the ZAYAZ federation.

AII serves as the measurable expression of the assurance architecture.

While TRACE establishes provenance, OARM validates reproducibility, AFLE enables federated assurance, DAL guarantees integrity, and AIATI generates assurance intelligence, AII converts those signals into a transparent and interpretable assurance score.

TRACE

Provenance

OARM

Verification

AFLE

Federation

DAL

Integrity

AIATI

Intelligence

AII

Assurance Score

AII functions as the assurance currency of the ECO Number Network.


2. Purpose

The Assurance Intelligence Index provides a standardized mechanism for evaluating:

  • trustworthiness
  • integrity
  • transparency
  • assurance maturity
  • reproducibility
  • ecosystem reliability

across organizations, suppliers, products, carbon passports, and federated assurance networks.

The objective is to transform millions of assurance events into a single, interpretable indicator suitable for:

  • management
  • auditors
  • regulators
  • investors
  • procurement teams
  • federation participants

3. Strategic Objectives

ObjectiveDescription
Assurance VisibilityMake assurance quality measurable
Trust BenchmarkingCompare assurance performance
Continuous ImprovementEncourage trust optimization
Federation IntelligenceMeasure ecosystem trust
Regulatory TransparencySupport defensible reporting
Carbon Passport ValidationMeasure passport quality
Risk AwarenessSurface emerging assurance risks
Governance SupportSupport policy and oversight

4. Core Concept

AII is not a trust score.

Trust is only one contributor.

AII measures the overall quality of an entity's assurance ecosystem.

Conceptually:

Trust
+
Integrity
+
Transparency
+
Verification
+
Provenance
+
Federation Quality
=
AII

5. Seven-Dimensional Assurance Model

Integrity

Measures:

  • data quality
  • schema compliance
  • validation performance
  • signal consistency

Primary Sources:

  • TrustGate
  • SSSR
  • DAL

Transparency

Measures:

  • lineage visibility
  • disclosure completeness
  • evidence accessibility
  • methodology documentation

Primary Sources:

  • TRACE
  • ZAR

Trust Accuracy

Measures:

  • trust prediction quality
  • confidence calibration
  • verifier agreement

Primary Sources:

  • TrustGate
  • AIATI

Verification Efficiency

Measures:

  • replay success rates
  • audit effort
  • verification throughput

Primary Sources:

  • OARM
  • AAE

Assurance Resilience

Measures:

  • recovery capability
  • anomaly response
  • governance maturity

Primary Sources:

  • DAL
  • AIGS

Provenance Quality

Measures:

  • lineage completeness
  • transformation transparency
  • replay reproducibility
  • traceability depth

Primary Sources:

  • TRACE
  • OARM

Federation Assurance

Measures:

  • attestation reliability
  • supplier trust
  • Carbon Passport verification
  • ecosystem consistency

Primary Sources:

  • AFLE
  • Carbon Passports

6. AII Formula

Conceptually:

AII=100×(wII+wTT+wAA+wVV+wRR+wPP+wFF)AII = 100 × (w_I I + w_T T + w_A A + w_V V + w_R R + w_P P + w_F F)

Where:

DimensionSymbolWeight
IntegrityII0.20
TransparencyTT0.15
Trust AccuracyAA0.20
Verification EfficiencyVV0.15
Assurance ResilienceRR0.10
Provenance QualityPP0.10
Federation AssuranceFF0.10
Total1.00

and:

Σ(w) = 1

Weights are version-controlled and governed through AIGS.


6.1. Dimensional Metrics

Integrity (I)

I=Verified DAL AnchorsTotal DAL AnchorsI = \frac{Verified\ DAL\ Anchors}{Total\ DAL\ Anchors}

Measures the percentage of ledger-anchored proofs verified as valid.


Transparency (T)

T=Disclosed CSIs+CMIs+SchemasTotal Required DisclosuresT = \frac{Disclosed\ CSIs + CMIs + Schemas}{Total\ Required\ Disclosures}

Evaluates how much of an organization’s data and logic is transparently documented and auditable.


Trust Accuracy (A)

A=1Mean(TrustpredictedTrustverified)A = 1 - {Mean(|Trust_{predicted} - Trust_{verified}|)}

Assesses the accuracy of predicted trust vs replay-verified outcomes.


Verification Efficiency (V)

V=Replays VerifiedReplays Initiated×1Normalized Audit CostV = \frac{Replays\ Verified}{Replays\ Initiated} \times \frac{1}{Normalized\ Audit\ Cost}

With output clipped to [0,1].

Balances verification success rate against effort or cost.


Assurance Resilience (R)

R=1σt(Trustverified)R = 1 - σ_t(Trust_{verified})

Measures temporal stability of verified trust scores (lower variance = higher resilience).


Provenance Quality (V)

TRACE-derived metric

Simple:

P=Complete Lineage RecordsTotal Required Lineage RecordsP = \frac{\text{Complete Lineage Records}}{\text{Total Required Lineage Records}}

Composite:

P=0.5L+0.3Tt+0.2RcP = 0.5L + 0.3T_t + 0.2R_c

Where:

  • LL = Lineage Completeness
  • TtT_t = Transformation Traceability
  • RcR_c = Replay Linkage Coverage

Federation Assurance (F)

AFLE-derived metric

Simple:

F=Verified Federated AttestationsTotal Federated AttestationsF = \frac{\text{Verified Federated Attestations}}{\text{Total Federated Attestations}}

Composite:

F=0.4Av+0.3Rs+0.3CvF = 0.4A_v + 0.3R_s + 0.3C_v

Where:

  • AvA_v = Attestation Validity
  • RsR_s = Cross-ECO Replay Success
  • CvC_v = Carbon Passport Verification Rate

7. Data Inputs

Data SourceRole in AIIExample Metrics
TRACEProvenance quality and lineage transparencyLineage completeness %, transformation coverage, replay linkage coverage
OARMVerification reproducibility and audit qualityReplay success %, verifier agreement, replay latency
AFLEFederation assurance qualityVerified attestation %, supplier assurance score, Carbon Passport validation rate
USOLineage and record integrityVerified lineage %, timestamp drift
ZARSoftware integrity and reproducibilityBuild hash match rate, version consistency
SSSRSchema completeness and metadata qualitySignal registration coverage, schema compliance
TrustGateTrust calibration qualityTrust prediction deviation, confidence calibration
DSAIL / AIATIAssurance intelligence qualityModel confidence growth, anomaly detection precision
ZSSRRouting effectivenessRouting success %, confidence match rate
DALCryptographic verification integrityAnchor validation %, proof verification success

8. AII Computation Cycle

PhaseFrequencyDescription
Data IngestionContinuousCollect trust, lineage, replay, federation, and verification telemetry
NormalizationHourlyNormalize metrics into standardized 0–1 scales using sector and domain baselines
Intelligence EnrichmentHourlyApply AIATI forecasts, anomaly indicators, and confidence adjustments
ComputationDailyCalculate dimensional scores and aggregate AII
VerificationDailyValidate methodology version, model references, and DAL integrity
PublishingWeeklyUpdate dashboards, benchmarks, leaderboards, and APIs
Audit LockQuarterlyFreeze AII state for reporting and assurance periods
Archival AnchoringQuarterlyAnchor official AII snapshots into DAL

9. Dimension-to-System Mapping

DimensionPrimary Sources
IntegrityDAL, TrustGate, SSSR
TransparencyTRACE, ZAR
Trust AccuracyTrustGate, AIATI
Verification EfficiencyOARM, AAE
Assurance ResilienceDAL, AIGS
Provenance QualityTRACE, OARM
Federation AssuranceAFLE, Carbon Passports

10. AIATI Contributions

AIATI continuously enriches AII through:

  • trust forecasts
  • anomaly detection
  • confidence calibration
  • federation risk analysis
  • Carbon Passport intelligence

Conceptually:

AIATI

Assurance Intelligence

AII

11. TRACE Contributions

TRACE contributes:

  • lineage completeness
  • transformation depth
  • provenance transparency
  • reproducibility quality

These indicators influence:

  • Transparency
  • Provenance Quality

dimensions.


12. OARM Contributions

OARM contributes:

  • replay success rates
  • verifier agreement
  • reproducibility scores
  • audit effort metrics

These indicators influence:

  • Verification Efficiency
  • Provenance Quality

dimensions.


13. AFLE Contributions

AFLE contributes:

  • attestation quality
  • supplier assurance maturity
  • federation trust propagation
  • cross-ECO verification outcomes

These indicators influence:

  • Federation Assurance

dimension.


14. Carbon Passport Intelligence

Carbon Passport assurance contributes:

  • passport verification rates
  • attestation validity
  • uncertainty levels
  • verifier acceptance rates

These metrics influence:

  • Federation Assurance
  • Trust Accuracy

dimensions.


15. Assurance Intelligence Data Model

FieldTypeDescription
eco_numbertextEntity being evaluated
domaintextDomain context
avg_trustnumericRolling trust mean
trust_deltanumericTrust trend
variancenumericConfidence interval width
audit_fail_ratenumericReplay failure rate
aii_scorenumericCurrent AII score
ai_recommendationjsonbRecommended actions
model_cmitextModel version used
dal_reftextDAL anchor reference
updated_attimestampLast recalculation

16. Example AII Records

Assurance Intelligence Record:

example-aii-record.jsonGitHub ↗
{
"eco_number": "ECO-A123",
"domain": "MICE",
"avg_trust": 0.87,
"trust_delta": -0.03,
"variance": 0.04,
"audit_fail_rate": 0.031,
"aii_score": 90.3,
"ai_recommendation": {
"action": "increase_manual_review",
"reason": "above-normal deviation detected",
"expected_trust_gain": 0.05
},
"model_cmi": "AII.Engine.Core.2_0_0",
"dal_ref": "DAL-2026-001245",
"updated_at": "2026-01-15T18:30:00Z"
}

Published AII Record:

example-published-aii-record.jsonGitHub ↗
{
"eco_number": "ECO-B456",
"period": "2026-Q1",
"integrity": 0.96,
"transparency": 0.89,
"trust_accuracy": 0.91,
"verification_efficiency": 0.83,
"assurance_resilience": 0.94,
"provenance_quality": 0.92,
"federation_assurance": 0.88,
"aii_score": 90.3,
"benchmark_percentile": 87,
"sector": "Manufacturing (C17.12)",
"confidence_interval": 0.02,
"methodology_version": "AII.2.0",
"dal_ref": "DAL-2026-001245",
"generated_at": "2026-01-15T18:30:00Z"
}

17. Scoring Bands

BandScore RangeDescription
A+ (Exemplary)90–100Fully verified, cryptographically anchored, continuous assurance.
A (Mature)80–89Consistent integrity, transparent schema, rare replays.
B (Reliable)70–79Verified trust but moderate variance in assurance cycle.
C (Developing)50–69Incomplete assurance coverage or inconsistent routing.
D (Provisional)0–49Low integrity or unverifiable proofs; flagged for audit.

18. DAL Anchoring of AII

All official AII calculations should be:

  • versioned
  • signed
  • replayable
  • DAL anchored

Example:

dal-anchoring-of-aii.jsonGitHub ↗
{
"aii_score": 90.3,
"methodology_version": "AII.2.0",
"dal_ref": "DAL-2026-001245",
"signature": "ed25519:..."
}

This ensures historical scores remain verifiable and defensible.


19. Computation Cycle

Operational Events

TRACE
OARM
AFLE
DAL

AIATI

AII Computation

Publication

Benchmarking

Improvement Actions

20. Outputs and Interfaces

InterfaceEndpointPurpose
AII API/aii/entity/{eco_number}Entity AII retrieval
Benchmark API/aii/benchmarkPeer comparison
Passport API/aii/passport/{id}Passport assurance score
Federation API/aii/federationNetwork-level scoring
Dashboard API/aii/dashboardVIZZ integration
Audit API/aii/audit/{eco_number}Historical AII evidence

21. Benchmarking

AII supports benchmarking across:

  • Organizations
  • Suppliers
  • Products
  • Carbon Passports
  • Industries
  • Regions
  • Federations

Benchmarking supports continuous improvement and ecosystem transparency.


22. Governance

AII methodology is governed through:

  • AIGS
  • EDAC
  • Assurance Governance Board
  • Federation Participants

Responsibilities include:

  • methodology approval
  • weighting review
  • bias monitoring
  • version management
  • auditability controls

23. Compliance Alignment

FrameworkRelevance
CSRDAssurance transparency
ESRSData quality and trust
ISO 14064-1Verification quality
ISO 14083Transport assurance
PAS 2080Supply-chain assurance
EU DPPProduct transparency
EU AI ActAI governance

24. Global Assurance Maturity Index (GAMI)

Viroway Ltd / ZAYAZ publishes the Global Assurance Maturity Index (GAMI) annually — a ranked aggregation of AII scores across industries and geographies based on sustained AII performance.

Recognition TierDescription
ECO DiamondAII ≥ 95, continuous verification for >12 months.
ECO PlatinumAII ≥ 90, complete data and code transparency.
ECO GoldAII ≥ 85, strong integrity and replay reliability.
ECO SilverAII ≥ 75, developing transparency and trust accuracy.
ECO BronzeAII ≥ 65, consistent basic verification compliance.

AII contributes to the Global Assurance Maturity Index (GAMI).

GAMI aggregates:

  • organizational AII
  • sector AII
  • federation AII
  • regional AII

to provide ecosystem-level assurance intelligence.

Example AII Snapshot (Top Entities)

RankECO NumberDomainAII ScoreIntegrityTrust AccuracyVerification Efficiency
1ECO-C981Manufacturing94.80.980.960.88
2ECO-B456Retail90.30.960.910.83
3ECO-A123Supply Chain88.40.940.890.80
4ECO-T112Logistics85.70.910.860.79
5ECO-F765Finance82.10.890.870.76

25. AII Dashboard Metrics (VIZZ Integration)

VIZZ visualizes both global and domain-level assurance intelligence:

VisualizationDescription
Global AII MapGeo-visualization of average AII by ECO region.
Trust Accuracy DriftLine chart of predicted vs verified trust deviations.
Verification Efficiency MatrixAudit ROI vs assurance success by sector.
DAL Anchor HealthRolling ledger verification rates.
AII Over TimeLongitudinal resilience graph by ECO entity.

25.1. AII Governance

RoleResponsibility
ZAYAZ Data Assurance Council (EDAC)Oversees model calibration, weighting, and fairness audits.
ZAYAZ AI Governance BoardReviews AI model bias and transparency.
External Assurance PartnersIndependently verify AII computation accuracy and methodology.
Eco Entities (ECO Nodes)Maintain their local lineage and trust data quality.

AII computations and methodologies are versioned and registered in ZAR (AII.Engine.Core.<version>).


25.2. Example SQL / Query API

example-aii-score-lookup.sqlGitHub ↗
SELECT
eco_number,
aii_score,
integrity,
transparency,
trust_accuracy,
verification_efficiency,
assurance_resilience,
benchmark_percentile
FROM aii_scores
WHERE period = '2025-Q3'
ORDER BY aii_score DESC;

API Endpoint:

GET /aii/{eco_number}?period=2025-Q3


26. Future Enhancements

Planned capabilities include:

  • Product-Level AII
  • Carbon Passport AII
  • Supply-Chain AII
  • Dynamic Federation AII
  • Predictive AII Forecasting
  • Autonomous Assurance Benchmarking
  • Regulatory Assurance Ratings
  • Real-Time AII Streaming

27. Summary

The Assurance Intelligence Index provides the measurable expression of assurance quality across the ZAYAZ ecosystem.

By combining:

  • TRACE provenance
  • OARM reproducibility
  • AFLE federation assurance
  • DAL integrity
  • AIATI intelligence
  • TrustGate trust evaluation

AII transforms complex assurance activity into a transparent, verifiable, and actionable assurance currency for the ECO Number Network.




GitHub RepoRequest for Change (RFC)