// EXECUTION_PIPELINE

Implementation Pipeline

Our engine handles the complexity of data movement while you focus on high-level decision logic.

PHASE_1 // Dynamic Run-Rate Calculation

Arcli ingests daily order volume and adjusts sales velocity based on recent micro-trends, ignoring stockout days.

PHASE_2 // Lead-Time Modeling

Input supplier lead times and safety buffer days at the SKU or vendor level.

PHASE_3 // Automated PO Triggers

Calculates the exact date to place a Purchase Order so inventory arrives precisely as current stock depletes.

PHASE_4 // Opportunity Cost Analysis

Visualizes exact Gross Profit bleeding per day on out-of-stock SKUs to justify expedited air freight.

// STRATEGIC_SCENARIO

Deep Data Retrieval

How Arcli grounds AI in your exact schema to generate highly-optimized, dialect-specific execution logic.

The Engine Room: Out-Of-Stock Excluded Velocity

How Arcli calculates true daily sales velocity by filtering out days where inventory was zero.

THE EXECUTIVE FILTER (ROI)

Ensures purchase orders are based on actual customer demand, preventing costly under-ordering caused by skewed data.

  • Fully optimized for DuckDB SQL (Embedded Execution) constraints.
  • Bypasses semantic layer hallucinations via strict schema grounding.
DuckDB SQL (Embedded Execution)_COMPILE
-- Generated by Arcli AI Semantic Router
WITH daily_sales AS (
    SELECT 
        sku,
        DATE_TRUNC('day', created_at) AS sale_date,
        SUM(quantity) as units_sold
    FROM tenant_workspace.shopify.order_lines
    GROUP BY 1, 2
),
daily_inventory AS (
    SELECT 
        sku,
        date,
        ending_inventory
    FROM tenant_workspace.shopify.inventory_snapshots
    WHERE ending_inventory > 0 -- The Arcli Secret: Exclude stockout days
),
true_velocity AS (
    SELECT 
        s.sku,
        AVG(s.units_sold) OVER (
            PARTITION BY s.sku 
            ORDER BY s.sale_date 
            ROWS BETWEEN 30 PRECEDING AND CURRENT ROW
        ) AS true_daily_velocity
    FROM daily_sales s
    JOIN daily_inventory i ON s.sku = i.sku AND s.sale_date = i.date
)
SELECT 
    sku,
    ROUND(MAX(true_daily_velocity), 2) AS adjusted_velocity_per_day
FROM true_velocity
GROUP BY 1
ORDER BY adjusted_velocity_per_day DESC;