The Fleet Vehicle Management sector in the DecisioQ Decision Catalog is identified by AUTO-FLEET. It supports decision support across dispatch, driver management, maintenance, compliance and safety, fuel and energy, cost control, digital operations, lifecycle planning, and business performance.

DecisioQ integrations should load sector, category, decision, Decision Preparation Model, and scenario metadata from the Decision Catalog. Do not hard-code old template codes, static decision lists, or legacy request models.

Recommended first deployment: start with one operational workflow where a ranked recommendation is useful but human review still matters, such as vehicle assignment, driver assignment, preventive maintenance priority, fuel exception approval, or replacement planning.

Fleet client applications should use the same discovery flow as the Business Decision Studio:

1. Load GET /decisioncatalog through the approved server-side Decision Catalog gateway.
2. Populate Sector from catalog.sectors[] and select AUTO-FLEET for Fleet Vehicle Management.
3. Populate Category from selectedSector.categories[]. Example categories include Driver Management, Compliance & Safety, Cost & Financial Control, Digital Operations, Fuel & Energy Management, Business Performance, Maintenance, Dispatch, and Lifecycle Planning.
4. Populate Decision from selectedCategory.decisions[] when available, or call /decisioncatalog/sectors/{sectorCode}/categories/{categoryCode}/decisions.
5. Display Decision Name only in the dropdown while keeping decisionId as the option value.
6. Load full decision detail from /decisioncatalog/decisions/{decisionId} before rendering Guided Data Collection.

Decision detail is the source of truth for criterion names, data guidance, scale, direction, profile options, scenarios, and overview metadata.

For regional deployments, keep DecisioQ technical identifiers stable and localize only user-facing labels and guidance. Unless the selected endpoint and decision schema explicitly support unit-qualified input, convert mileage, distance, pressure, temperature, mass, volume, speed, fuel consumption, and other measurements to the required canonical units before submission. Do not infer units or currency from locale.

Fleet integrations should map vehicle, driver, route, maintenance, telematics, fuel, compliance, and financial data into decision-specific Business Data. The selected decision detail defines which criteria are required and how each value should be measured.

Do not invent criterion IDs. Use the canonical criteria returned by /decisioncatalog/decisions/{decisionId}, including criterion overview metadata, unit, direction, scale, and data guidance.

Production integrations should keep credentials and bearer tokens on trusted servers or server-side gateways. Browser pages should use same-origin proxy handlers or their own backend service.

1. Trusted backend obtains a JWT token from identity.vinquery.com.
2. Application loads catalog and decision detail metadata.
3. User or system prepares Business Data for candidate vehicles, drivers, routes, maintenance jobs, fuel options, compliance cases, or lifecycle actions.
4. Call POST /api/v1/validate to validate and prepare the decision input before execution.
5. Call POST /api/v1/decide to return the authoritative Decision Result.
6. Display the recommendation, ranked alternatives, warnings, assumptions, and Explanation of Decision Result.
7. Keep execution trace and diagnostics available to integrators, but collapsed or hidden by default for business users.

Use /api/v1/decide for both Prepared Criteria Mode and business-data integrations that submit a businessData object. New public onboarding should prefer Preview Decision and Execute Decision terminology.

The exact fields depend on the selected Fleet Vehicle Management decision. The example below shows the integration style rather than a guaranteed schema for every decision.

{
  "decisionId": "AUTO-FLEET-009",
  "decisionPreparationModelId": "AUTO-FLEET-PROFILE-STANDARD",
  "scenarioId": "AUTO-FLEET-SCENARIO-DRIVER-ASSIGNMENT",
  "businessData": {
    "candidates": [
      {
        "optionId": "DRIVER-1842",
        "name": "Driver A - local delivery route",
        "values": {
          "availabilityScore": 91,
          "certificationMatchScore": 96,
          "hoursOfServiceScore": 82,
          "safetyScore": 88,
          "routeFamiliarityScore": 79,
          "overtimeRiskScore": 24
        }
      },
      {
        "optionId": "DRIVER-2057",
        "name": "Driver B - regional delivery route",
        "values": {
          "availabilityScore": 86,
          "certificationMatchScore": 92,
          "hoursOfServiceScore": 74,
          "safetyScore": 91,
          "routeFamiliarityScore": 84,
          "overtimeRiskScore": 37
        }
      }
    ]
  },
  "requestContext": {
    "correlationId": "fleet-dispatch-20260717-001"
  }
}

This pattern belongs in a trusted backend, not directly in browser JavaScript.

async function executeFleetDecision(decisionInput, jwtToken) {
  const response = await fetch(`${process.env.DECISIOQ_BASE_URL}/api/v1/decide`, {
    method: "POST",
    headers: {
      "Authorization": `Bearer ${jwtToken}`,
      "Content-Type": "application/json"
    },
    body: JSON.stringify(decisionInput)
  });

  if (!response.ok) {
    throw new Error(`DecisioQ execution failed: ${response.status} ${await response.text()}`);
  }

  return await response.json();
}

• Store identity credentials, Decision API base URL, and proxy configuration in trusted server configuration or a secret manager.
• Do not expose bearer tokens or integration credentials in browser code.
• Use catalog metadata rather than hard-coded categories, decisions, criteria, profiles, or scenarios.
• Validate Business Data before execution and show user-friendly validation messages.
• Persist correlation ID, vehicle ID, driver ID, route ID, work order ID, decision ID, profile ID, scenario ID, selected option, score, and explanation for audit.
• Retain the successful decision response requestId with the host business transaction, then call POST /api/v1/decision-outcomes when the action and realized result are known.
• Require an overrideReason for overridden recommendations; never infer acceptance merely because a result was displayed.
• Monitor GET /api/v1/decision-outcomes/summary for acceptance rate, override rate, and realized-value aggregates. Treat outcome feedback as reporting evidence, not automatic model training.
• Redact driver identifiers, location traces, safety notes, customer route details, and sensitive cost data in logs and diagnostics.
• Monitor catalog load failures, token refresh failures, API latency, validation failures, account verification failures, and unusual exclusion rates.
• Define fallback behavior so dispatch, maintenance, safety, and compliance workflows remain usable when DecisioQ is unavailable.
• Review Decision Preparation Models and scenario assumptions with operations, maintenance, safety, and finance owners when policies or operating conditions change.