Cabier Global Assurance · Architecture
Assurance Corpus and Assurance Intelligence
An assurance system that reasons only by calling a general-purpose model has a structural problem: it depends on the same class of intelligence it is meant to assure. The foundation layer exists to remove that dependency.
The Cabier Assurance Corpus is the structured knowledge foundation. Cabier Assurance Intelligence is a specialised reasoning layer developed and evaluated against it, and it is deliberately model-independent.
Published as reference architecture. The corpus contents, evaluation methodology and reasoning implementation are proprietary and are not published.
Horizontal ontology
Twenty-four object classes that recur in every regulated and high-consequence setting, whatever the sector calls them.
Vertical overlays
The sector changes the obligations and the language. It does not change the object model.
Financial services
Prudential, conduct, financial crime, payments, resilience and market integrity obligations.
Insurance
Underwriting, pricing, claims conduct, capital and reserving.
Legal
Privilege, confidentiality, conflicts and professional duty.
Healthcare
Clinical safety, patient data, device and decision-support duties.
Government and public sector
Public accountability, procurement, records and national residency expectations.
Critical infrastructure
Operational technology, continuity, incident duties and national resilience.
Digital assets
Custody, settlement, reserve assurance and tokenised instrument obligations.
Cybersecurity
Access, detection, response, reporting clocks and third-party dependency.
Energy
Reliability, safety, environmental duty and dispatch integrity.
Industrial and logistics
Safety, provenance and physical-system authority.
Social and algorithmic platforms
Systemic risk assessment, content and recommender accountability, minors, transparency and researcher access.
Relationships, not documents
The corpus preserves relationships rather than storing source material as disconnected documents. A single chain has to read end to end: law, obligation, entity, system, model, agent, authority, control, evidence, outcome. That is what makes a conclusion derivable rather than asserted.
What the intelligence layer reasons about
- Cabier Assurance Intelligence is a specialised assurance reasoning layer. It is not a general-purpose frontier model and does not compete with frontier providers on general intelligence.
- It is model-independent by design. It may draw on Cabier models, open-weight models, customer-controlled models, approved frontier models, deterministic reasoning, statistical methods and graph reasoning.
- No single external model is a mandatory dependency. Cabier must never depend exclusively on the intelligence provider it is assuring.
- It is developed and evaluated against the Cabier Assurance Corpus, leaving the implementation route open across retrieval, graph reasoning, specialised models, distillation, human feedback and synthetic evaluation.
Assurance intelligence independence
An assurance decision must be capable of being produced through deterministic controls, TrustGraph, the Assurance Corpus, Cabier Assurance Intelligence, independent model evaluation and human authority, rather than requiring any one frontier model. That is the answer to who assures the assurer.
Deterministic controls
The mechanical part of an assurance decision resolves without inference at all.
TrustGraph
Relationships, dependencies and propagation are read from the graph, not guessed.
Assurance Corpus
Structured authority, obligation, control and evidence knowledge with preserved relationships.
Cabier Assurance Intelligence
Specialised reasoning where the answer is a judgement rather than a lookup.
Independent model evaluation
More than one assessment for high-consequence questions, so no single model is the arbiter.
Human authority
A named person or committee holds the consequential decision. Assurance prepares it.
The assurance learning cycle
Eight steps, with the important constraint stated immediately after them.
Observe
Behaviour, permissions, obligations, dependencies and evidence freshness.
Evaluate
Against the control set and the evaluation requirements for that consequence class.
Decide
Through the Trust Gates, with the disposition stating its basis.
Review
Human review where the consequence class or the ambiguity requires it.
Evidence
The decision, its basis and its outcome recorded and dated.
Outcome
What actually happened, including refusals, interventions and near misses.
Learn
Reviewed outcomes improve the corpus and subsequent evaluation through a governed pipeline.
Reassess
The assurance position is recomputed rather than assumed to still hold.
- Production decisions do not automatically become training data.
- Material entering the corpus passes a governed pipeline: provenance, approval, privacy controls and versioning.
- Customer and institutional material is used only within the permissions granted for it, and residency constraints travel with it.
- Every corpus version is identified, so a past conclusion can be re-derived against the knowledge that existed at the time.
The spine
How a consequential action moves through the architecture, and what sits underneath it.
- 01
Frontier, enterprise and sovereign AI
The systems entering the environment, whatever their provenance.
- 02
AssureAdapt
Consequence-driven assurance routing. Sets both assurance intensity and computational intensity.
- 03
Deterministic controls, TrustGraph and Assurance Intelligence
Three parallel inputs to the decision, so no single one is a required dependency.
- 04
AssureCore
The eight Trust Gates and the disposition, with governing facts, authority, controls, evidence and escalation condition.
- 05
AssureMark
Evidence and provenance, written as machine-readable assurance context with an expiry.
- 06
Human and institutional authority
Where consequential decisions are taken. Assurance prepares them, it does not replace them.
- 07
Assurance state
The current, dated, derivable position, and the movement in the institution's resilience position.
Foundation
Cabier Assurance Corpus
Horizontal ontology and vertical domains, with relationships preserved.
Cabier Assurance Intelligence
Developed and evaluated against the corpus. Model-independent and model-diverse.
Continuous learning, evaluation and reassessment
Governed pipeline, versioned, with human-reviewed outcomes only.
Assurance of the assurance system
AI is assured by Cabier. Cabier's own assurance mechanism is assured through evidence, testing, governance and human authority. The recursion is manageable because it terminates in the same place every institutional control does: a named human accountable for a dated decision.
Where the same reasoning is applied to interaction effects across an interconnected ecosystem.
See the systemic layer