Import and Distribution

Importer and Distributor of Furniture and Luggage from China

Import and International Trade — Furniture and Luggage from China

We replaced purchase-order management from China that ran on scattered spreadsheets in Drive with a single system that tracks every order from the production stage through to inventory receipt — and alerts you when to reorder before a product runs out.

Client's existing dashboard

Supabase

AI API

Accounting system

Suppliers / factories in China

Challenge

The Challenge

The importer brings in furniture and luggage from China through around 10 suppliers, with long lead times of up to 120 days. Order management was handled through scattered spreadsheets in Drive: the owner couldn't remember what had been ordered from which supplier, there was no organized tracking of each order's status (in production / ready / at sea / received into inventory), and there was no way to plan future orders based on actual sales pace. At the same time, inventory worth ₪2–3 million was stuck, and orders weren't aligned with the performance of specific models and colors — a situation that simultaneously caused shortages of in-demand products and surplus stock that wasn't moving.

Solution

The Solution

We built a commerce and inventory environment that connects the operating dashboard, WooCommerce and customer service. The purchasing module creates supplier orders, consolidates products into containers, calculates landed cost and forecasts shortages from sales pace and inbound inventory. In parallel, WooCommerce workflows identify abandoned carts and send WhatsApp reminders, synchronize inventory into Supabase and alert on low stock. A multi-user service workspace and customer bot use the same customer and shipment data.

Our Approach

A purchase-order (PO) module for suppliers, drawn from the product catalog in the dashboard — quantities, purchase prices, deposits, order ID and dynamic fields such as a swatch number per color

Split status tracking: purchasing ← in production ← ready ← at sea ← inventory receipt, with the ability to split an order across several statuses in parallel

A container entity for consolidating items from multiple orders from the same supplier, with automatic per-unit shipping cost calculation and a landed-cost display per product

An inventory forecasting engine that weighs sales pace against current inventory + in production + in transit, and alerts to shortage risk with a recommended quantity and order date

AI recommendations and interactive dialogue while building the proforma, based on model and color performance — including a recommendation of which products are most urgent to load into the upcoming container

A settings page the client manages on their own — production and shipping times and changing operational parameters — including automatic measurement of actual transition times to update the forecast

Filters and cross-section views by supplier, category, model and status — including comparing the same category across several suppliers in a single view

Inventory receipt with an organized data structure for an entry note, an organized Excel export for feeding into the accounting system, and a data infrastructure ready for a future API connection on the client's side

WooCommerce abandoned-cart detection and a WhatsApp reminder connected to the existing customer journey

WooCommerce-to-Supabase inventory synchronization, low-stock alerts and a multi-user service workspace with customer and shipment data

Technologies Used

Client's existing dashboardSupabaseAI APIAccounting systemSuppliers / factories in China

The service behind this project

Automation for Businesses

Results

The Results

The system replaces spreadsheet management and gives full visibility into every order at every stage — from production in China through to inventory receipt. The client already works with the dashboard on an ongoing basis, and the purchasing module was built on top of it and expanded beyond the initial version. The goals defined with the client: zero orders forgotten or lost, a reduction of up to 70% in order-management time, and prevention of inventory shortages through data-based forecasting alerts. Because lead times are measured automatically in practice, forecasting accuracy is expected to improve as the system accumulates history.

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