Qualification and outcomes

Prove technical control first, then measure whether the workflow improves wholesale operations

Reference evaluation and production business outcomes are deliberately separated. A synthetic run can qualify correctness and control; it cannot establish live productivity, service-level or ROI improvement.

Reference qualification model

Salesorder AI qualification and production measurement framework

The reference implementation separates reproducible technical qualification from live business outcomes. Synthetic benchmark values are publishable only when backed by a versioned run artifact; productivity and ROI remain production measurements.

Qualification
1,500 cases Ground-truth corpus design Versioned test population spanning retrieval, exception logic, conflicting evidence, abstention and protected actions
150 cases Protected-action suite Authorization, stale-state and protected-write scenarios requiring zero bypass for release
Required Production business baseline Investigation time, rework, escalation and exception ageing must be measured before business-impact claims

Operating assumptions

  • The AI enablement environment uses synthetic transactional records modelled on wholesale ERP workflows.
  • The benchmark contains 1,500 versioned requests with known expected evidence, calculations, permissions and outcomes.
  • Salesorder transactional services remain the source of truth; the model does not become an order, inventory or warehouse system of record.
  • Production productivity, service-level and ROI outcomes require validation with authorised live data and users.

Qualification matrix

MeasureMethodPopulationRelease gateProduction use
Entity / context resolutionExact expected order, customer, SKU and warehouse scopeApplicable ground-truth casesThreshold defined before run; ambiguity must abstainDetect retrieval drift and wrong-record risk
Tool selection & input accuracyExpected tool set and validated parameters per test caseTool-bearing evaluation casesCritical tools and parameters must passDetect orchestration regressions
Numerical fidelityDeterministic recomputation of outstanding, available, allocated and shortage quantitiesNumeric cases100% target for protected calculationsDetect quantity/calculation defects
Blocker classificationExpected exception class vs system classificationKnown exception casesPredefined acceptance threshold; critical classes separately gatedMonitor operational diagnosis quality
Evidence completenessMandatory evidence references present and source versions capturedEvidence-bearing cases100% target for protected recommendationsDetect unsupported explanations
Grounded explanationClaims trace to retrieved evidence and deterministic rule resultsExplanation casesNo material unsupported operational claimMonitor hallucination / grounding risk
Correct abstentionSystem withholds conclusion when identity, evidence or authority is incomplete/conflictingDesigned abstention casesCritical abstention cases must passMonitor unsafe overreach
Authorization enforcementProtected requests and actions checked against authenticated role and action policy150 protected-action tests plus production protected actions0 authorization bypassesSecurity control effectiveness
Pre-execution revalidationOrder/inventory/rule versions re-read before approved writeAll prepared protected actions100% requiredPrevent stale-state execution
Trace completenessRequired identity, source, tool, rule, recommendation, approval and action fields capturedAll evaluation and production runs100% for protected workflowsAuditability and incident reconstruction

Security and governance qualification targets

Protected action without authenticated authority0 permitted
Approval token accepted after relevant state/version changes0 permitted
Direct model write to order, inventory or shipment tables0 permitted
Protected execution without correlation/audit trace0 permitted

Agent evaluation qualification targets

Intent / entity resolutionMeasured against expected order, customer, SKU and warehouse context
Tool selection and tool-input accuracyExpected tools and parameters evaluated per test case
Deterministic numerical fidelity100% target for protected quantity calculations
Groundedness and evidence completenessNo protected recommendation without mandatory evidence
Correct abstentionCritical incomplete/conflicting-evidence cases must abstain
Authorization and stale-state controlsZero bypass in protected-action suite

Act with Approval qualification targets

Approved actions revalidated immediately before execution100%
Direct model writes to transactional tables0

Bounded automation qualification targets

Read-only shadow review completed before action permission expansionRequired gate
Material exception silently resolved without policy/authority0

Learn & Improve qualification targets

Confirmed defects converted to versioned regression cases100%
Critical authorization regression allowed to release0
Business KPIPre-AI baselineControlled rollout measureHow change is calculated
Median exception investigation timeMeasured from representative human casesMeasured from assisted cases with same start/stop definitionPilot median vs baseline median
Records/screens manually consultedObserved/telemetry count per caseManual views remaining after evidence assemblyMean/median reduction by exception class
First-pass blocker accuracyReviewed human disposition sampleReviewed assisted investigation sampleCorrect first disposition / reviewed cases
Escalation rateEscalated exceptions / investigated exceptionsSame denominator during controlled rolloutRate change with severity slice
Rework / reopen rateReopened or corrected resolved exceptions / resolved casesSame definition in pilotRate change; lower is better
Exception ageingTime from exception open to permitted next actionSame definition in pilotMedian and tail percentile change
Unauthorized protected actionsProduction audit countProduction audit countMust remain zero
Evidence-complete investigationsCases containing required source/version referencesSame definition in pilotCompleteness rate
Rollout stageWhat is allowedEvidence required to progress
0 · BaselineHuman process only; instrument representative exceptionsStable KPI definitions and reviewed ground truth
1 · Read-only shadowAgent investigates; no operational recommendation/action dependencyAgreement with reviewed outcomes; failure analysis complete
2 · Assisted investigationUsers receive evidence and explanationQuality/security gates pass; user review captured
3 · RecommendationPolicy-permitted options shownUnsupported recommendation and abstention gates pass
4 · Prepare actionAction package created but not executedApproval path, scope and idempotency validated
5 · Controlled executionApproved bounded action after live-state revalidationSecurity suite, stale-state tests, audit and rollback/recovery controls pass
Production outcome claims require a defined population, period, baseline, measurement method and source. Until those exist, the case reports qualification status rather than invented productivity percentages.

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