Cabier Global Assurance · Architecture

    AssureAdapt

    Assurance that has to be configured by hand for every new environment will always arrive after the system it was meant to govern. AssureAdapt is the adaptive layer: it discovers what is running, works out what it is, what it can do, who controls it, which rules apply, and then derives the assurance position for that specific combination.

    It adapts two things at once. Assurance intensity, which is how much scrutiny the activity warrants, and computational intensity, which is how much reasoning is spent reaching the answer. Both follow consequence, uncertainty, environmental change and evidence freshness.

    Published as reference architecture. The trigger logic, routing thresholds and control derivation rules are set per engagement.

    The cycle

    Ten steps, continuous rather than annual. The loop never ends on assured; it ends on reassess.

    01

    Discover

    Find what is actually running: models, systems, agents, tools, tool servers, credentials and the data each one can reach.

    02

    Identify

    Resolve identity and ownership. A system without a named owner cannot hold authority.

    03

    Classify

    Place the activity in a consequence class and record what a failure would cost, to whom.

    04

    Map

    Attach the entity, activity, data, jurisdictions and applicable authority through the relationship graph.

    05

    Configure

    Derive the control set, evaluation requirements, permission envelope and evidence expectations for that combination.

    06

    Assure

    Establish the current assurance state with dated evidence rather than an assumption carried forward.

    07

    Monitor

    Observe behaviour, permissions, dependencies, obligations and evidence freshness continuously.

    08

    Detect change

    Register the difference rather than the alarm. Most consequential change is undramatic.

    09

    Adapt

    Re-derive controls, evaluation, permissions and intensity for the changed condition.

    10

    Reassess

    Recompute the assurance position and route what a person must decide to a person.

    What makes the position move

    Seven triggers. None of them requires an incident. Most consequential change is quiet: a permission widened, a version shipped, a provider becoming critical.

    An AI system gains financial authority

    Payment, trading, posting or treasury reach moves the activity into a higher consequence class immediately.

    An agent gains access to sensitive data

    The permission envelope, isolation controls and evidence requirements are all re-derived.

    A model is upgraded or replaced

    Capability changed, so prior evaluation evidence is no longer current for the new version.

    A new jurisdiction enters scope

    Users, entity, data or inference in a new place changes which rules apply, cumulatively.

    A new regulation or supervisory expectation appears

    Obligations are re-mapped to the existing control set and the gap is stated rather than absorbed.

    A third-party provider becomes critical

    Concentration and dependency change the resilience position even when nothing failed.

    AI begins interacting with a physical system

    Operational technology adjacency raises assurance intensity and constrains autonomous action.

    Consequence-driven routing

    The reason this is affordable at scale. Most activity never needs specialised reasoning at all, and the activity that does is the activity worth spending it on.

    Routine activity

    Deterministic and local

    Policy, permission and control checks resolve in the environment itself, with no external reasoning and no data leaving the boundary.

    Elevated activity

    Graph and statistical reasoning

    Relationship traversal, dependency analysis and baseline deviation carry the assessment.

    Ambiguous or high-risk activity

    Cabier Assurance Intelligence

    Specialised reasoning over authority, obligation, control, evidence and consequence, where the answer is not mechanical.

    Exceptional, frontier or high-consequence activity

    Multi-model evaluation and human authority

    More than one independent assessment, then a named person or committee decides. Assurance intensity and computational intensity rise together.

    AssureAdapt decides how hard to look. AssureCore decides what happens at the moment of a consequential action.

    See the decision boundary