Azure DevOps Demo Models · main
catalog.json

catalog.json · 5,789 bytes · read-only public source view
{
  "schemaVersion": "1.0",
  "name": "MyEzAI ModelOps Demo Model Catalogue",
  "repositoryPurpose": "Public demonstration models only; no customer or confidential model code.",
  "defaultBranch": "main",
  "models": [
    {
      "modelKey": "life-reserve-projection",
      "displayName": "Life Insurance Reserve Projection",
      "industry": "Insurance",
      "technology": "Python",
      "version": "2.1.0",
      "criticality": "High",
      "path": "insurance/life-reserve-projection",
      "engineKey": "life-reserve",
      "description": "Projects premiums, claims, expenses and statutory reserves under base and stress assumptions.",
      "tags": [
        "Actuarial",
        "Valuation",
        "IFRS 17",
        "Stress testing"
      ]
    },
    {
      "modelKey": "pension-funding-projection",
      "displayName": "Public Pension Funding Projection",
      "industry": "Government",
      "technology": "Fortran",
      "version": "4.3.0",
      "criticality": "Critical",
      "path": "government/pension-funding-projection",
      "engineKey": "pension-funding",
      "description": "Projects pension assets, liabilities, contributions and funded status over a long-term horizon.",
      "tags": [
        "Pension",
        "Government",
        "Fortran",
        "Long-term projection"
      ]
    },
    {
      "modelKey": "credit-portfolio-stress",
      "displayName": "Credit Portfolio Stress Test",
      "industry": "Banking",
      "technology": "R",
      "version": "1.8.0",
      "criticality": "High",
      "path": "banking/credit-portfolio-stress",
      "engineKey": "credit-stress",
      "description": "Calculates stressed expected credit losses by exposure segment and macroeconomic scenario.",
      "tags": [
        "Credit risk",
        "ECL",
        "Banking",
        "Scenario analysis"
      ]
    },
    {
      "modelKey": "public-benefit-cost-forecast",
      "displayName": "Public Benefit Cost Forecast",
      "industry": "Government",
      "technology": "C#/.NET",
      "version": "3.0.0",
      "criticality": "High",
      "path": "government/public-benefit-cost-forecast",
      "engineKey": "public-benefit",
      "description": "Forecasts program beneficiaries, average benefit and annual government expenditure.",
      "tags": [
        "Public policy",
        "Benefits",
        "Fiscal forecast",
        ".NET"
      ]
    },
    {
      "modelKey": "hospital-capacity-forecast",
      "displayName": "Hospital Capacity and Wait-Time Forecast",
      "industry": "Healthcare",
      "technology": "Python",
      "version": "1.5.0",
      "criticality": "High",
      "path": "healthcare/hospital-capacity-forecast",
      "engineKey": "hospital-capacity",
      "description": "Forecasts admissions, bed occupancy and wait-time pressure under demand and staffing scenarios.",
      "tags": [
        "Healthcare",
        "Capacity planning",
        "Wait times",
        "Operations"
      ]
    },
    {
      "modelKey": "electricity-demand-forecast",
      "displayName": "Electricity Demand Forecast",
      "industry": "Energy & Utilities",
      "technology": "R",
      "version": "2.4.0",
      "criticality": "Medium",
      "path": "energy/electricity-demand-forecast",
      "engineKey": "energy-demand",
      "description": "Projects peak electricity demand using growth, weather and electrification assumptions.",
      "tags": [
        "Energy",
        "Load forecast",
        "Utilities",
        "Climate scenario"
      ]
    },
    {
      "modelKey": "inventory-reorder-optimization",
      "displayName": "Inventory Reorder Optimization",
      "industry": "Manufacturing",
      "technology": "Python",
      "version": "1.2.0",
      "criticality": "Medium",
      "path": "manufacturing/inventory-reorder-optimization",
      "engineKey": "inventory-reorder",
      "description": "Calculates economic order quantities, reorder points and safety stock under service-level targets.",
      "tags": [
        "Supply chain",
        "Inventory",
        "Optimization",
        "Manufacturing"
      ]
    },
    {
      "modelKey": "retail-demand-markdown",
      "displayName": "Retail Demand and Markdown Planner",
      "industry": "Retail",
      "technology": "C#/.NET",
      "version": "1.7.0",
      "criticality": "Medium",
      "path": "retail/retail-demand-markdown",
      "engineKey": "retail-markdown",
      "description": "Estimates weekly unit demand, revenue and margin across promotional markdown scenarios.",
      "tags": [
        "Retail",
        "Pricing",
        "Demand",
        "Margin"
      ]
    },
    {
      "modelKey": "vba-routine-assessment",
      "displayName": "VBA Routine Assessment and Migration",
      "industry": "Model Modernization",
      "technology": "Python + VBA",
      "version": "1.0.0",
      "criticality": "Medium",
      "path": "modernization/vba-routine-assessment",
      "engineKey": "vba-assessment",
      "description": "Inventories VBA procedures, complexity indicators, external dependencies and migration candidates.",
      "tags": [
        "VBA",
        "Excel",
        "Modernization",
        "Code assessment"
      ]
    },
    {
      "modelKey": "university-enrollment-forecast",
      "displayName": "University Enrollment Forecast",
      "industry": "Education",
      "technology": "Bash + Python",
      "version": "1.3.0",
      "criticality": "Low",
      "path": "education/university-enrollment-forecast",
      "engineKey": "enrollment-forecast",
      "description": "Projects applications, yield, continuing students and total enrollment by planning scenario.",
      "tags": [
        "Education",
        "Enrollment",
        "Planning",
        "Forecast"
      ]
    }
  ]
}