A local-first Python tool that optimizes order fulfillment across multiple fulfillment centers. It matches multi-item customer orders against warehouse inventory balances using configurable strategies (priority, nearest_zone, or no_split), generating exact dispatch manifests, courier shipment routing, and shortage exception logs before you send orders to the warehouse floor.
orders.csv (order lines with customer delivery pincodes/zones) and warehouse_inventory.csv (stock by warehouse ID).
Local Python script evaluates fulfillment strategies (no_split, nearest_zone, priority), verifies stock balances, and decrements inventory.
allocation_manifest.csv (orders mapped to warehouses), warehouse_balances.csv, and shortage_exceptions.csv.
Setup scope covers installation on customer-controlled infrastructure, configuration of authorised integrations, functional testing and handover.
Hosting, third-party charges and ongoing support are excluded unless separately agreed. Free workflows must never run on Sanocea-hosted infrastructure.
When managing stock across multiple warehouses or retail stores, multi-item orders are often split haphazardly across distant facilities, doubling courier freight charges and frustrating customers with disjointed deliveries.
Split shipments destroy ecommerce operating margins by paying two courier delivery fees for a single order. Inefficient warehouse allocation also increases delivery transit times.
Evaluates each incoming order against stock levels across all regional warehouses, tests allocation rules (nearest_zone, highest_stock, or no_split), and assigns items to the lowest-cost fulfillment path.
Your dispatch team receives a unified warehouse allocation manifest that consolidates orders into single shipments and eliminates guesswork.
Shows how the allocation engine fulfills an order from a single facility instead of causing an expensive split shipment.
Order #501 (Zone North): Item A (Qty 2), Item B (Qty 1)
Stock:
WH-DELHI: Item A (5), Item B (10) [Zone North]
WH-MUMBAI: Item A (10), Item B (0) [Zone West]order_id,item_id,allocated_warehouse,quantity,shipping_zone,strategy_used,split_count
501,Item A,WH-DELHI,2,North,nearest_zone,1
501,Item B,WH-DELHI,1,North,nearest_zone,1All items consolidated into WH-DELHI. Customer receives one package; merchant avoids paying double courier shipping charges.
Technical Setup Guidance:
Every deliverable is clean, self-contained, and ready for immediate deployment. You receive the complete files, configuration templates, setup guides, and automated tests.
| File Name | Deliverable Description |
|---|---|
allocator.py | Core multi-warehouse allocation and routing engine |
run.sh | Execution wrapper script |
requirements.txt | Test execution requirements (standard library only for runtime) |
README.md | Operational usage guide & schema specifications |
SETUP.md | Step‑by‑step local setup instructions |
COSTS.md | Zero recurring cost declaration |
LICENSING.md | Sanocea Commercial License |
tests/test_allocator.py | Pytest suite covering all allocation rules and edge cases |
data/inventory.csv | Sample multi-warehouse inventory dataset |
data/orders.csv | Sample unfulfilled customer orders dataset |
For technical teams or developers assisting your business, below is the visual execution architecture and automated verification breakdown:
The script reads multi-warehouse stock balances and unfulfilled order CSVs, runs split-shipment minimization logic, prioritizes hub nodes, matches customer delivery zones, and exports allocations, shortage audits, and warehouse picklists. Zero external network calls are made.
Prioritizes routing complete orders to a single capable facility to eliminate multi-parcel carrier costs
Configurable allocation by minimum split, facility priority rank, regional zone matching, or stock balancing
Detects out-of-stock items and unknown SKUs, exporting structured shortage manifests
We believe in complete transparency. Review the documented technical boundaries and external service fee breakdown below prior to obtaining the package:
| Component | Estimated Cost | Details & Free Tier Allowances |
|---|---|---|
| Multi-Warehouse Allocation Toolkit | ₹0 (Free to self-host) | Download full source code and self-host |
| Optional Assisted Setup | ₹500 one-time | Assisted installation, environment setup, and handover |
| Hosting & Third-Party Fees | ₹0 recurring | Standard Python local execution, no third-party APIs needed |
Receive the complete distributable archive containing allocator.py, step-by-step setup guides, mock fixtures, and automated test suites.
Setup scope covers installation on customer-controlled infrastructure, configuration of authorised integrations, functional testing and handover.
Hosting, third-party charges and ongoing support are excluded unless separately agreed. Free workflows must never run on Sanocea-hosted infrastructure.
By default, the engine executes the 'no_split' heuristic: for every order, it evaluates all candidate warehouses to find any single facility capable of fulfilling 100% of line items. Only when no single location holds sufficient stock does it fall back to multi-node split shipments.
Yes. Each warehouse row includes an optional priority integer (e.g. 1 for central distribution hub, 2 for regional depot). When multiple warehouses can fulfill an order, the engine automatically selects the highest-priority facility.
No. The allocator runs 100% locally on your machine using Python standard library components. There are zero cloud compute fees, database server prerequisites, or recurring software charges.
The engine logs all unfulfillable units to a structured shortages.csv manifest, detailing the exact order ID, SKU, missing quantity, and root cause (such as INSUFFICIENT_GLOBAL_STOCK or UNKNOWN_SKU) without corrupting running inventory balances.
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