WikiSure — The semantic foundation of meaning
The knowledge graph WikiSure governs: approved business definitions, the governance concepts that make them durable, and the AI concepts that depend on them.
Meaning is the shared interpretation a term has across the people, systems and AI that use it. In an enterprise, meaning is what determines whether a decision is consistent or not.
Meaning is the foundation of AI Alignment
AI systems can only be aligned if they share the same meaning of business terms.
Meaning is captured as Business Definitions
business definitions are the atomic units of governed meaning.
Meaning is anchored by Canonical Definitions
a canonical definition is the one approved meaning every actor resolves to.
Meaning is enforced through Meaning Resolution
meaning is only useful when conflicting interpretations can be resolved against an approved source.
drift is what happens when meaning is left ungoverned.
Meaning is governed by Semantic Governance
semantic governance is the discipline that keeps meaning stable over time.
Shared meaning is the state in which humans, systems and AI agents — across teams, partners and ecosystems — interpret the same business term in the same approved way. It is the substrate that turns coordination into trust.
AI agents can only align on outcomes once they share the meaning of the terms they act on.
Shared Meaning is composed of Business Definitions
shared meaning is the aggregate of approved business definitions.
Shared Meaning is the public form of Meaning
shared meaning is meaning extended beyond a single organisation.
Shared Meaning is sustained by Meaning Resolution
shared meaning persists only when conflicts are continuously resolved against the approved source.
Shared Meaning is governed by Semantic Governance
semantic governance is the discipline that produces and preserves shared meaning.
A business definition is the approved meaning of a critical business term — such as Risk, Customer, Claim or Incident — captured in one place, owned by an accountable person and made available to humans, systems and AI in the same form.
Business Definitions is required for AI Alignment
AI systems need stable definitions to behave consistently across decisions.
Business Definitions is published as Canonical Definitions
the approved business definition is the canonical one that downstream actors must resolve to.
Business Definitions enables Meaning Resolution
an approved definition is the source of truth against which conflicts are resolved.
Business Definitions prevents Semantic Drift
without one approved definition, terms quietly take on different meanings in different places.
Business Definitions is the practice of Semantic Governance
governing definitions is the operational form of semantic governance.
A canonical definition is the single approved version of a business term — versioned, owned by an accountable person and made available in the same form to humans, applications and AI agents.
Canonical Definitions is required for AI Alignment
AI agents can only stay aligned when they all resolve to the same canonical version.
Canonical Definitions is the approved form of Business Definitions
the canonical definition is the published version of the business definition.
Canonical Definitions enables Meaning Resolution
resolution requires a canonical version to resolve conflicting interpretations against.
Canonical Definitions prevents Semantic Drift
if there is only one canonical version, alternative interpretations cannot quietly take its place.
Canonical Definitions is governed by Semantic Governance
governing the canonical version is how semantic governance is exercised in practice.
Meaning resolution is the act of taking a term whose interpretation differs across teams, systems or AI and resolving it against the one approved business definition.
Meaning Resolution is necessary for AI Alignment
AI systems can only stay aligned if their interpretations are continuously resolved against the approved meaning.
Meaning Resolution depends on Business Definitions
resolution requires one approved definition to resolve against.
Meaning Resolution resolves to Canonical Definitions
every resolution ends at the canonical version of the term.
Meaning Resolution reverses Semantic Drift
resolution actively re-aligns interpretations that have drifted apart.
Meaning Resolution operationalizes Semantic Governance
resolution is how semantic governance is enforced in day-to-day operations.
Semantic drift is the silent divergence of meaning that happens when the same business term is independently re-defined across teams, applications, contracts, dashboards and AI models.
AI systems become unreliable when business terms lose stable meaning.
Semantic Drift is prevented by Business Definitions
approved definitions remove the ambiguity that allows drift to start.
Semantic Drift is countered by Canonical Definitions
a single canonical version leaves no room for parallel interpretations to take hold.
Semantic Drift is corrected by Meaning Resolution
resolution actively realigns interpretations that have drifted.
Semantic Drift is addressed by Semantic Governance
semantic governance is the discipline of keeping meaning stable over time.
Semantic governance is the discipline of governing the meaning of business terms across humans, systems and AI — so every actor in the enterprise resolves to the same approved definition.
Semantic Governance enables AI Alignment
AI systems can only align on outcomes when they first align on meaning.
Semantic Governance is built on Business Definitions
approved business definitions are the unit of governance.
Semantic Governance publishes Canonical Definitions
governance is exercised by maintaining the canonical version of every term.
Semantic Governance is enforced through Meaning Resolution
governance has no effect unless conflicts can be resolved against the approved source.
Semantic Governance is the answer to Semantic Drift
governance exists to stop drift from quietly eroding shared meaning.
AI alignment is the practice of ensuring that AI systems behave consistently with the organization's intent — including the meaning of the business terms they reason about.
AI Alignment depends on Business Definitions
AI cannot stay aligned without one approved meaning per business term.
AI Alignment resolves to Canonical Definitions
AI agents must resolve to the canonical version of every term they reason about.
AI Alignment requires Meaning Resolution
AI agents need a way to resolve ambiguous terms against the approved definition at runtime.
AI Alignment is broken by Semantic Drift
AI Alignment is the foundation of Semantic Governance
governance of meaning is what makes AI alignment achievable in an enterprise.
Meaning Infrastructure is the layer that captures, governs and serves the approved meaning of business terms to every human, system and AI agent in the enterprise. It treats meaning the way modern enterprises treat identity or data: as a first-class infrastructure layer, not as documentation scattered across decks and wikis.
Meaning Infrastructure is required by AI Agent Governance
agents can only be governed when there is an infrastructure layer they can resolve meaning against.
Meaning Infrastructure serves Canonical Definitions
the infrastructure layer is what makes the canonical version reachable to every consumer.
Meaning Infrastructure is the foundation of Enterprise Meaning Management
managing meaning across the enterprise is only feasible on top of a real infrastructure layer.
Meaning Infrastructure exposes Meaning Resolution
resolution is the runtime contract that meaning infrastructure offers to applications and agents.
Meaning Infrastructure is operationalized by Semantic Governance
governance only takes effect when meaning is exposed as infrastructure that systems can call.
AI Agent Governance is the discipline of ensuring that every AI agent acting inside the enterprise resolves shared business terms to the same approved meaning — and that its decisions can be traced back to that meaning.
agent governance is the discipline that constrains how agents resolve meaning.
AI Agent Governance extends AI Alignment
agent governance is alignment applied to autonomous systems acting inside the enterprise.
AI Agent Governance requires Meaning Infrastructure
agents need an infrastructure layer to call when resolving terms.
AI Agent Governance depends on Meaning Resolution
agents must resolve terms at runtime against the approved meaning to stay governed.
AI Agent Governance is the agentic form of Semantic Governance
governing agents is how semantic governance is applied to the agentic layer.
Enterprise Meaning Management is the practice of managing the lifecycle of approved meanings — proposal, approval, versioning, resolution, retirement — across the whole enterprise, so every team, system and AI agent operates from the same semantic baseline.
Enterprise Meaning Management enables AI Agent Governance
without enterprise-wide management of meaning, agent governance cannot hold.
Enterprise Meaning Management manages Business Definitions
approved business definitions are the unit being managed across the enterprise.
Enterprise Meaning Management runs on Meaning Infrastructure
managing meaning at enterprise scale requires a real infrastructure layer underneath.
Enterprise Meaning Management is the operating model of Semantic Governance
governance is the discipline; enterprise management is how it is run day-to-day at scale.
Enterprise Meaning Management produces Shared Meaning
the outcome of managing meaning across the enterprise is shared meaning between all actors.
A customer is a party that has an active commercial relationship with the organization. The exact scope — prospect, active, lapsed, household, legal entity — varies by team and system.
Customer is governed as Business Definitions
Customer is one of the highest-impact business definitions in any enterprise.
regulatory obligations apply to customers, so the customer scope must be unambiguous.
policies are issued to customers, so policy reporting depends on a stable customer definition.
every customer relationship implies an exposure that must be assessed consistently.
Risk is the possibility of an adverse outcome that affects the organization, its customers or its obligations. Different functions measure it differently: probability, exposure, severity, capital impact.
AI risk models must align on a shared definition of risk to be trustworthy.
exposure is one of the components used to express risk.
incidents are how risk materialises and is measured ex-post.
policies are priced against a specific definition of risk.
A claim is a formal request for compensation or service under an existing policy or contract. Its scope depends on lifecycle stage, coverage, reserves and recoveries.
claims data feeds regulatory and solvency reporting.
claims consume the exposure carried under a policy.
an incident is the underlying event that gives rise to a claim.
claims only exist in the context of an underlying policy.
An incident is an event that affects operations, customers or obligations and may require a response. Its scope spans operational, security, safety and customer events.
incidents are typically the trigger event for claims.
many incidents trigger regulatory reporting obligations.
controls exist to detect, prevent or mitigate incidents.
incidents are how risk materialises in the real world.
A policy is a contractual agreement that defines the rights, obligations and coverage between the organization and a counterparty. Its scope spans status, endorsements, renewals and product variants.
the policy defines the basis on which claims can be made.
every policy is bound to a customer whose definition must also be stable.
policies are the primary carrier of exposure in the portfolio.
every policy is an instantiation of a product definition.
A partner is an external party that participates in the value chain — brokers, distributors, reinsurers, service providers, technology vendors — under a defined relationship.
regulatory obligations often extend to the conduct of partners.
controls over partners are how partner-related risk is managed.
policies are typically sold and serviced via partners.
partner relationships introduce third-party risk that must be governed.
A product is an offering the organization brings to market under a defined structure of features, pricing, coverage and rules. Its scope changes with variants, bundles and lifecycle stages.
Product is governed as Business Definitions
Product is one of the most reused business definitions across the enterprise.
products are subject to regulatory approval and disclosure rules.
products are positioned and sold to customer segments that must be defined consistently.
policies are the operational instantiation of products.
Compliance is the practice of meeting legal, regulatory and internal obligations. Most obligations are expressed in business language whose meaning must be unambiguous.
AI systems used in regulated processes must align on compliant definitions.
Compliance is operationalized by Control
controls are how compliance obligations are executed day-to-day.
many incidents trigger specific compliance obligations.
Compliance depends on Semantic Governance
compliance becomes defensible only when the meaning of terms is governed.
A control is a deliberate mechanism that prevents, detects or mitigates a risk. Every control implicitly relies on definitions of the entities it acts on.
controls are how compliance obligations are operationalized.
controls exist to prevent, detect or mitigate incidents.
controls are the practical response to defined risks.
control effectiveness depends on stable meanings of the entities controlled.
Exposure is the quantified extent to which the organization stands to be affected by an adverse outcome. It can be expressed in monetary, capacity or contractual terms.
claims consume the exposure carried under policies.
controls are designed against defined exposure thresholds.
policies are the carriers of exposure in the portfolio.
exposure is one of the primary ways risk is measured.
Approval is the act by which an accountable owner certifies that a business definition is the one the organization will operate against. It transforms a candidate definition into the authoritative one.
approval is the moment accountability for a definition is fixed.
Approval promotes a definition to Canonical Definitions
approval is what turns a candidate definition into the canonical one.
only an accountable owner can issue an approval that holds.
Approval is an act of Semantic Governance
approval is one of the core operational acts of semantic governance.
Ownership is the assignment of a named, accountable party responsible for the meaning of a business term — its content, its currency and its resolution.
ownership is how accountability for meaning is made concrete.
the owner is the party empowered to approve a definition.
owners are the stewards of business definitions over time.
no governance regime works without clearly assigned owners.
Accountability is the property that, for every approved business definition, there is a named party answerable for its meaning, its currency and the decisions taken on its basis.
the approval record is where accountability is captured.
Accountability is required by Compliance
regulators require accountability for the definitions used in reporting.
Accountability is the goal of Governance
governance exists to produce demonstrable accountability.
Accountability is made concrete by Ownership
ownership is the operational expression of accountability for a definition.
Consistency is the property that the same business term carries the same approved meaning across every team, system, contract and AI agent that uses it.
Consistency is the foundation of Alignment
alignment between humans, systems and AI starts from consistent meaning.
Consistency is produced by Canonical Definitions
consistency follows automatically when every actor resolves to the canonical definition.
Consistency is enforced by Meaning Resolution
resolution is how consistency is achieved at runtime.
drift is the gradual loss of consistency that resolution exists to reverse.
Governance is the system of ownership, approval and oversight by which an organization manages how decisions are made. Applied to meaning, it determines what business terms mean and who can change them.
Governance is exercised through Approval
approvals are how governance decisions about meaning are recorded.
compliance is one of the regimes that depends on governed meaning.
governance is exercised by named owners, not by committees alone.
Governance is specialised as Semantic Governance
semantic governance is the application of governance to meaning itself.
Alignment is the state in which humans, systems and AI agents act on the same intent — starting from the same definitions of the business terms involved.
Alignment is the AI-specific form of AI Alignment
AI alignment is alignment extended to autonomous systems.
alignment is impossible without consistent meaning across actors.
alignment starts with shared meaning of the terms in play.
Alignment is enabled by Semantic Governance
governance of meaning is what makes durable alignment possible.
An AI agent is an autonomous or semi-autonomous system that interprets inputs, reasons about business concepts and takes actions on the organization's behalf.
agents acting in the enterprise must be aligned on the meaning of business terms.
agents need a way to resolve ambiguous terms at runtime against approved meaning.
agents resolve terms through the same resolution layer that humans and systems use.
ungoverned agents are a fast source of new semantic drift inside the enterprise.
Context resolution is the act of selecting the approved meaning of a business term for the specific context in which it is used — a process, a contract, a regulatory regime, an AI agent's task.
Context Resolution is required by AI Agent
agents need contextual resolution to behave correctly across different tasks.
Context Resolution selects from Canonical Definitions
context resolution picks the canonical definition that applies to the situation.
Context Resolution is the contextual form of Meaning Resolution
context resolution narrows generic resolution to the specific context of use.
Context Resolution is governed by Semantic Governance
context-specific meanings must themselves be approved and governed.
Shared Meaning → Shared Understanding → Trusted Collaboration → SynsureTech
WikiSure governs one approved meaning per term, inside the enterprise.
Parties that resolve to the same definitions can interpret the same situation the same way.
Shared understanding is the precondition for collaboration that does not require reconciliation.
SynsureTech is the Coordination Graph. It extends trusted collaboration across enterprise boundaries — on top of the Meaning Graph WikiSure has already governed.