Glossary¶

Canonical terms used across this site, the product, and Venturi’s governed documentation. When a page and this glossary disagree, treat the glossary as the intended vocabulary and tell us.

Attribution¶

Attribution graph: The connected representation of AI usage and organizational responsibility. Venturi resolves usage across six layers: model invocation, service, code ownership, identity, organizational hierarchy, and budget.
RAIL: Venturi’s reconciliation and attribution pipeline. Three stages: Stage A deterministic entity resolution, Stage B attribution inference, Stage C fractional cost allocation. See RAIL pipeline.
Attribution coverage: The share of capturable AI usage that resolves through the required attribution chain at or above the confidence floor. Venturi reports coverage against an honest denominator; it never claims complete visibility.
Pathway: A distinct route by which AI usage reaches your enterprise (managed provider APIs, cloud-hosted model services, self-hosted models, AI embedded in SaaS, automation platforms). Each pathway has its own capture mechanism.
Unknown / Shared / Unresolved: Explicit attribution outcomes. Unknown means the evidence does not identify an owner; Shared means multiple owners legitimately split responsibility; Unresolved means conflicting evidence is awaiting reconciliation. None of these are hidden, zeroed, or silently guessed.
Multi-truth model: Usage, cost, and ownership are recorded as distinct truths. A single event can be certain in one dimension and provisional in another.
Ownership vs allocation: Two distinct relationships in the attribution graph: ownership is a direct single-owner edge, allocation is a fractional split across several owners. Keeping them separate stops shared responsibility from collapsing into a false single-owner answer.

Confidence¶

Confidence score (coper): The operational confidence attached to every attribution result, capped at 0.95 as a deliberate policy ceiling. It is never called accuracy or certainty. See Confidence and evidence.
Confidence bands: chargeback_ready (confidence at or above 0.80), provisional (0.50 to 0.79, labeled and never auto-billed), and estimated (below 0.50, excluded from chargeback).
Evidence card: The per-result explanation of which signals produced an attribution and at what confidence, available wherever a result is shown.
Posterior confidence (cpost): The uncapped model-internal confidence preserved for training, audit, and analysis. It is never shown on operational surfaces, which display only the capped coper.

Enforcement posture¶

Decision-time interceptor: The fail-open component on the AI request path that observes usage at decision time. It adds bounded latency and can never block customer AI traffic by failing: on any fault or timeout it passes traffic through and records null attribution.
Shape mode: The default advisory posture. Venturi recommends; your systems and people decide.
Gate mode: The explicit, scoped, opt-in hard-stop capability. Gate issues an authenticated deny recommendation to an enforcement point that you manage; Venturi never silently denies traffic in-line, and Gate is rollback-aware.
Fail-open / fail-closed: The interceptor data path fails open (customer AI traffic is never blocked by Venturi unavailability). Everything else fails closed: authentication, authorization, tenant isolation, admin actions, exports, and billing.
Policy evaluation record: The audit event written when a governance policy evaluates an invocation or attributed record, making advisory and enforcement behavior reviewable after the fact.
Manual override record: The audit event recording a human override of an attribution or policy outcome, preserving the intervention as evidence rather than mutable state.

Deployment¶

Control plane: The vendor-managed surface used for licensing, signed updates, configuration metadata, and governed orchestration. Deliberately separate from the data plane so raw telemetry never has to leave your infrastructure.
Data plane: The customer-side runtime containing ingestion, processing, graph state, materialization, and decision-time serving — where your operational data lives and where attribution computation runs.
Customer trust boundary: The boundary inside which customer telemetry, event processing, graph state, and materialized indexes remain unless explicitly exported.
Read-only integrations: Customer system connectors default to read behavior (get, list, describe) and never mutate your systems; a platform gate blocks any connector module that requests write access from shipping.

Cost and value¶

Chargeback-eligible: A cost line whose attribution confidence is at or above the 0.80 floor. Lines below the floor are labeled provisional or estimated and are never auto-billed.
Identified savings vs realized savings: An identified saving is an opportunity the platform has found; a realized saving is one you have captured, verified against a frozen baseline. The two are never conflated.
TRAC: Total Risk-Adjusted Cost: billed cost plus a confidence risk premium plus carbon liability — spend adjusted for the uncertainty and externality context of the usage behind it.
Cost derivation method: The per-record field describing how a cost value was derived — direct billing evidence, calibrated estimation, or another explicit method — so measured spend is never conflated with inferred spend.
FOCUS export: Cost export pinned to the FinOps Open Cost and Usage Specification v1.2, with Venturi extension columns. See Reporting and exports.

Value metrics¶

Gross AI value: The total measured value attributed to AI before any cost is subtracted: measured financial value, plus measured productivity value, plus included inferred-productivity value. The top of the cost/value waterfall.
Net AI value: Gross AI value minus AI spend and the explicit quality and risk adjustments — the honest bottom line of the cost/value waterfall.
ROI: Net AI value divided by AI spend, computed at query time and undefined when spend is zero — never served as a precomputed ratio.
Cost per successful outcome: AI spend divided by the count of accepted outcomes, computed at query time and undefined when there are no accepted outcomes, so cost is judged against value actually delivered.
Quality-adjusted savings: Optimization savings scaled by the realized quality adjustment factor, so a savings figure is never claimed at full value when output quality regressed.

Data handling¶

Metadata-only capture: Venturi’s default: invocation metadata is captured, prompt and completion content is not. There is no content field in the event schema.
k-anonymity floor (k = 5): Aggregated views never expose groups smaller than five people. Individual- level visibility exists only behind an explicit legal gate and is off by default.
Crypto-shred: Erasure by destroying the per-subject or per-tenant encryption keys, backed by a deletion certificate.
Break-glass access: The only support access path: time-boxed, MFA-gated, audit-logged, and visible to you. There is no standing support access.

Product surfaces¶

Projection: A decision surface derived from the attribution graph (for example the chargeback view or the coverage map), not a standalone module.
Adoption intelligence: Attributed usage signals about organizational uptake of AI, reported cohort-only. It is not HR analytics and is never used for individual performance scoring.
Decision surface state: The maturity label on a product surface: observe-only (informational), decision-support (human-guided decisions with caveats), or operationally trusted (evidence quality supports tighter operational reliance).
Fan-out warning: A dashboard warning that one upstream action appears to be triggering a disproportionately large volume of downstream AI calls, so multiplied cost is investigated rather than misread as normal demand.
Model Energy Rating: The star rating shown on model energy surfaces, derived from measured watt-hours. See Energy methodology.
System of record: A destination Venturi is building toward, not a status it claims today.