Trusted
Evidence supports the commitment and its meaning remains intact.
The frameworkBusiness meaning to
Business meaning to
Decision Trust.
TRUST Architecture preserves business meaning across enterprise systems and converts governed evidence into defensible Decision Trust States.
The core question: has enterprise meaning survived every transformation?
Six canonical components
The computational architecture.
Select a component to see its role, its output, and its place in the weekend overtime example.
Component 01 / 06
Meaning Unit
Define the business commitment whose meaning must survive as it moves across systems.
What it produces
A canonical business commitment with a clear grain, decision context, and baseline for traceability.
Example: Weekend overtime performed by EMP-102 on work order WO-8821.
Governance runs through the architecture.Decision context, business rules, evidence requirements, and remediation guide each evaluation.
The decision outputFive states.
Five states.
A visible rationale.
A trust state expresses what the evidence supports at an evaluation point. Corrective action leads to a new evaluation rather than an assumed recovery.
Risky
Integrity signals indicate a risk that needs investigation.
Broken
A confirmed integrity failure disrupts meaning or relationships.
Unverifiable
Available evidence is insufficient to support a trust conclusion.
Recovered
A supported correction and re-evaluation establish recovery.
Integrity signal engineering
From system events to evidence leadership can use.
TRUST evaluates how business meaning changes, encodes integrity conditions, and links the resulting signals to evidence.
Data engineering, machine learning, contextual intelligence, and analytics support the architecture.
Azure Data FactoryMachine learning / XGBoostVocabulary intelligencePower BI
- Relationship coherence
Validate that the operational context remains connected through payroll and financial posting.
- Engineered integrity signals
Identify anchor gaps, allocation drift, missing approvals, and payroll-to-GL variance.
- Contextual vocabulary intelligence
Use governed descriptions and narratives to recover context, with confidence and contributing evidence visible.
- Governed trust classification
Apply defined rules and evidence requirements to produce a trust state and its rationale.
The architecture in contextOne overtime event.
One overtime event.
A chain of consequences.
The work-order relationship explains why the labor cost belongs to production. Losing that anchor can change its financial interpretation even when payroll and the general ledger reconcile.
This illustrative example shows where TRUST makes the break, impact, and required evidence visible.
Operational reality
Trusted- Employee
- EMP-102
- Work order
- WO-8821
- Activity
- Weekend overtime
- Labor classification
- Direct production labor
The work order links the overtime to the production activity. That relationship carries the business meaning.
Questions from leadership
Putting TRUST to work.
Does TRUST replace our ERP, payroll, or reporting platform?
TRUST introduces a governed decision integrity layer across existing systems and data platforms. The diagnostic identifies the data, relationships, and controls required for the selected decision context.
How is this different from reconciliation?
Reconciliation checks whether numbers agree. TRUST also evaluates whether the relationships and business meaning behind those numbers survived each transformation, and whether the evidence supports the decision.
How does AI fit into the architecture?
The framework combines governed rules, integrity-state encoding, vocabulary intelligence, and machine learning where appropriate. Any prediction or inferred context needs supporting evidence, confidence, and human review within the agreed decision process.
What happens when evidence is missing?
The architecture makes the evidence gap visible. A commitment can remain Unverifiable until the evidence is sufficient. A model inference alone does not establish recovery.
How do we start?
Start with a Diagnostic Fit Check, followed by a 3–4 week Decision Integrity Diagnostic if there is a suitable decision context and accessible evidence.
Ready to find where margin risk is hiding?
Start with a conversation about the decisions your reporting needs to support.