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ZYZ-EVI-01 — Enterprise Value Intelligence (EVI)

Status​

Draft Constitutional Specification

Version 0.1

1. Purpose

Enterprise Value Intelligence (EVI) is the constitutional framework governing how ZAYAZ transforms assured sustainability information into decision-support outputs.

The purpose of EVI is not to predict enterprise value.

Its purpose is to ensure that every value-related output generated by ZAYAZ has a clearly defined epistemic foundation, transparent provenance, explicit assumptions, and an appropriate level of confidence.

This specification establishes what kinds of statements the platform is permitted to make.

2. Constitutional Principle

The value of ZAYAZ is not that it produces more numbers.

The value of ZAYAZ is that every number can be trusted.

Trust is achieved by making every output explicitly traceable to:

  • verified evidence
  • deterministic computation
  • declared assumptions
  • or external authority

No output shall present a higher level of certainty than its underlying evidence supports.

3. Design Philosophy

EVI is not primarily a financial engine.

It is a Decision Intelligence framework.

Financial metrics are only one possible consumer of assured sustainability information.

Other consumers include:

  • executive management
  • lenders
  • insurers
  • regulators
  • investors
  • procurement
  • auditors
  • customers
  • public authorities

Accordingly, EVI publishes Decision Objects, not merely financial metrics.

4. Core Principle — Epistemic Classification

Outputs are classified by how they are known, not by the business domain they belong to.

This distinction is fundamental.

The platform must never treat deterministic regulatory calculations and scenario-based financial projections as equivalent classes of information.

5. Output Taxonomy

Class A — Verified Facts​

Information directly supported by assured evidence.

Characteristics:

  • Gatehouse verified
  • traceable
  • deterministic
  • auditable
  • filing-grade

Examples:

  • Scope emissions
  • Energy consumption
  • Supplier verification
  • Water withdrawals
  • Material composition
  • Carbon inventories

Class B — Derived Computations​

Outputs calculated deterministically from verified facts using publicly defined rules.

Characteristics:

  • reproducible
  • deterministic
  • regulation-backed
  • fully explainable
  • audit-grade

Examples:

  • Carbon exposure
  • ETS liabilities
  • CBAM obligations
  • Tax exposure
  • Regulatory exposure
  • Future compliance liabilities

Typical data sources:

  • Gatehouse assured facts
  • Pergamum Pulse regulatory intelligence
  • Published legislation
  • Official calculation methodologies

Class C — Scenario Projections​

Outputs generated using explicit modelling assumptions.

Characteristics:

  • assumption-driven
  • reproducible
  • explainable
  • sensitivity-aware
  • not deterministic

Examples:

  • EBITDA impact
  • Cash flow
  • NPV
  • IRR
  • Enterprise value scenarios
  • Investment prioritisation

Every Scenario Projection shall include:

  • assumptions
  • methodology
  • version
  • confidence interval
  • sensitivity analysis

Scenario outputs shall never be presented as verified facts.

Class D — Directional Insights​

Analytical recommendations generated from statistical or AI-assisted reasoning.

Characteristics:

  • non-deterministic
  • explainable
  • advisory
  • confidence-scored

Examples:

  • suggested investment priorities
  • optimisation opportunities
  • supply-chain recommendations
  • decarbonisation pathways

Directional Insights support decision making but are not evidence.

Class E — Evidence Packages​

Structured collections of assured information prepared for consumption by external institutions.

Characteristics:

  • verified
  • machine-readable
  • reusable
  • institution-ready

Consumers include:

  • banks
  • insurers
  • investors
  • procurement systems
  • regulators
  • certification bodies

Typical formats:

  • API payloads
  • JSON
  • XBRL
  • PDF assurance reports
  • digital evidence packages

The purpose of an Evidence Package is not to replace external decision-makers.

Its purpose is to provide trustworthy inputs into their own models.

Class F — External References​

Information originating from external institutions.

Examples:

  • ESG ratings
  • Credit ratings
  • Insurance assessments
  • Market valuations

These values may be referenced.

They shall never be represented as native ZAYAZ computations.

6. Decision Constraints

EVI shall support governance-aware decision making.

Not every output is a recommendation.

Some outputs describe constraints.

Examples:

  • regulatory prerequisites
  • missing supplier verification
  • incomplete assurance
  • permit expiry
  • taxonomy eligibility blockers

Constraint Objects communicate whether an action is currently permissible rather than whether it is financially attractive.

7. Trust Before Precision

Whenever uncertainty exists, ZAYAZ shall reduce apparent precision rather than overstate confidence.

The platform shall always prefer:

  • transparent assumptions
  • explicit uncertainty
  • explainable reasoning

over false numerical accuracy.

Trust has constitutional priority over precision.

8. What EVI Does Not Do

EVI does not:

  • issue credit ratings
  • predict insurance premiums
  • replace investment analysts
  • replace lenders' internal models
  • replace actuarial models
  • replace market pricing

Instead, EVI produces the highest-quality assured information those models require.

The objective is to make sustainability information bankable, not speculative.

9. Architectural Position

Universal Signal Ontology (USO)
            │
            ▼
Input Hub
            │
            ▼
Gatehouse Assurance
            │
            ▼
Pergamum Pulse
(Regulatory Intelligence)
            │
            ▼
Computation Hub
            │
            ▼
Enterprise Value Intelligence (EVI)
            │
            ▼
Decision Objects
            │
            ├── Verified Facts
            ├── Derived Computations
            ├── Scenario Projections
            ├── Directional Insights
            ├── Evidence Packages
            └── Constraint Objects

EVI is therefore a constitutional computation layer positioned between computational engines and downstream consumers.

10. Constitutional Rule

Every Decision Object published by ZAYAZ shall expose:

  • provenance
  • confidence class
  • methodology
  • assumptions (if applicable)
  • evidence lineage
  • regulatory references (where applicable)
  • version
  • audit trace

No Decision Object may omit its confidence classification.

11. Guiding Principle

ZAYAZ does not compete with institutions that price risk.

ZAYAZ provides the world's most trustworthy sustainability intelligence for those institutions to consume.

The platform's competitive advantage is not prediction.

It is assured decision intelligence.



GitHub RepoRequest for Change (RFC)