Customers browse a catalog and order via WhatsApp; the AI parses free-text order messages into structured orders and tracks status through fulfillment.
Small online sellers (Instagram/WhatsApp-based shops) manage orders manually inside chat threads, causing missed or incorrect orders.
Customers browse a catalog and order via WhatsApp; the AI parses free-text order messages into structured orders and tracks status through fulfillment.
GPT parses natural-language orders ("2 red shirts size M, deliver to Gulshan") into structured line items matched against the catalog.
Fewer order errors, a real order log instead of scattered chats, and automated status updates to customers.
Click below to simulate the deployed product. Every field is customizable at delivery.
| Red kurta · Size M | 2 × PKR 2,400 |
| White kurta · Size L | 1 × PKR 2,600 |
| Delivery Karachi | PKR 250 |
| Total | PKR 7,650 · COD |
These are captured in the confirmation form after purchase. Every product ships with these fields exposed in a settings page.
catalog_items (id, user_id, name, price, stock) whatsapp_orders (id, user_id, customer_phone, items_json, total, status, address) order_status_log (id, order_id, status, timestamp)
Full Lovable + Supabase project structure with Edge Function templates for WhatsApp / AI / cron.
Step-by-step Supabase project setup, API key placement, WhatsApp Business linking, first-run test.
customize.json for brand, business name, language, tone. .env.example for all API keys.
Self-host on your Supabase in ~15 min, or opt into DSR-managed VPS at checkout.