SynergyLogix API Documentation

Sample Python Request

import requests

url = "https://api.jandojegs.com/v1/predict-demand"
headers = {
    "Authorization": "Bearer YOUR_API_KEY",
    "Content-Type": "application/json"
}

payload = {
    "product_id": "SKU-12345",
    "location": "US-WEST",
    "forecast_horizon": 30,  # days
    "historical_data": {
        "sales": [120, 135, 142, 156, 148],
        "dates": ["2025-01-01", "2025-01-02", "2025-01-03", "2025-01-04", "2025-01-05"]
    },
    "external_factors": {
        "seasonality": true,
        "promotions": [],
        "weather_impact": "moderate"
    }
}

response = requests.post(url, json=payload, headers=headers)
forecast = response.json()
print(forecast)

Response Schema

{
  "status": "success",
  "product_id": "SKU-12345",
  "location": "US-WEST",
  "forecast": {
    "predictions": [
      {
        "date": "2025-02-01",
        "demand": 165,
        "confidence_interval": {
          "lower": 142,
          "upper": 188,
          "confidence_level": 0.95
        },
        "risk_score": 0.23  // 0-1 scale, lower is better
      }
      // ... 29 more days
    ],
    "model_metrics": {
      "accuracy": 0.94,
      "mean_absolute_error": 8.2,
      "trend": "increasing"
    },
    "insights": [
      "Expected 12% demand increase due to seasonal factors",
      "Low stock-out risk detected",
      "Recommend increasing safety stock by 15%"
    ]
  },
  "recommendations": {
    "optimal_inventory": 2450,
    "reorder_point": 450,
    "safety_stock": 180
  }
}

Additional Endpoints