GlossaryThe vocabulary, defined

Words that carry weight.

Operational intelligence has a vocabulary, and most of it is used loosely. These are our canonical definitions — written to be quoted, argued with, and held against the systems that claim them.

01

Operational intelligence

Operational intelligence is the continuous fusion of an organisation's live signals — workforce, supply, energy, compliance, security — into decisions that are drafted with evidence and approved by humans. Where business intelligence reports on what happened, operational intelligence acts on what is happening.

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02

Evidence-bound autonomy

Evidence-bound autonomy is an architecture for AI agents in which no consequential action executes until the agent has produced its evidence: the signals it read, the policy it applied, the reasoning it followed, and the reversibility it can guarantee — sealed into a tamper-evident record before the action, not after.

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03

Policy-by-proof

Policy-by-proof is the enforcement model in which written policy defines the boundary of what an AI agent may do autonomously, and every action at that boundary must carry a proof of compliance with the policy that permitted it. Policy is not documentation of intent; it is the executable perimeter of autonomy.

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04

Proof packet

A proof packet is the typed, signed, replayable record an AI agent must produce before a consequential action executes: the inputs read, the policy clauses consulted, the reasoning chain followed, the systems the action will touch, and the human or policy that authorised it — chained into a tamper-evident ledger.

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05

Decision lineage

Decision lineage is the complete, traceable path of a decision: backward from the action to the reasoning, policy, and source signals that produced it, and forward from the action to its downstream outcome. A decision with lineage can be audited, replayed, and defended; a decision without it can only be remembered.

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06

Audit-grade ledger

An audit-grade ledger is a hash-linked, tamper-evident record of every decision and action a system takes, designed to survive adversarial review — an inspector general, a regulator, a forensic audit. Each entry is chained to the previous one, so alteration of any record is detectable by construction.

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07

Human-in-the-loop (HITL)

Human-in-the-loop is the design principle that consequential AI actions require human authorisation at the moment of consequence — as an engineered gate with the evidence attached, not as an exception handler. The human is not a fallback for the system; the human is the authority the system reports to.

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08

Deterministic AI

Deterministic AI is an architecture for regulated decisions in which the determination is computed by executable rules over structured facts — producing the same verdict from the same facts, every time — while probabilistic models handle what they are good at: extracting structure from unstructured reality. The property purchased is repeatability under scrutiny.

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09

Neuro-symbolic AI

Neuro-symbolic AI combines neural models (perception, extraction, language) with symbolic systems (rules, logic, ontologies) so that each does the work the other cannot: neural components read the messy world, symbolic components guarantee consistent reasoning over it. In regulated domains it is the practical path to AI that is both capable and defensible.

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10

Operational ontology

An operational ontology is a typed, machine-readable model of an organisation's world — its entities, relationships, policies, and classifications — that gives AI systems a shared vocabulary grounded in how the operation actually works. It is the load-bearing structure beneath reliable automation: rules, agents, and analytics all inherit its definitions.

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11

Machine-readable rules

Machine-readable rules are regulations, codes, or policies encoded as executable logic — with effective dates, jurisdictional scope, and citations preserved — so that compliance can be evaluated mechanically and repeatably. The rule remains law; the encoding makes it computable.

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12

Data residency & sovereign deployment

Data residency is the guarantee that data is stored and processed within a specified jurisdiction; sovereign deployment extends the guarantee to the whole system — models, runtime, and operations run inside infrastructure the owning institution controls, up to fully air-gapped environments. For public-sector AI in Canada, residency is the entry requirement, not a differentiator.

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13

Decision intelligence

Decision intelligence is the discipline of engineering how organisations make decisions: modelling the decision itself — its inputs, its logic, its authority, its outcome — rather than only the data around it. Its unit of work is a decision with evidence, not a chart with implications.

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