SupplyAI - AI-Powered Efficiency for Your Supply Chain
The Supply Chain Management (SCM) application is designed to streamline the procurement, shipping, and sales processes for businesses. It provides end-to-end visibility and control over the supply chain, from placing orders for supplies to choosing shipment options and selling products through platforms like Amazon or Shopify. The application incorporates AI features to optimize costs, manage unexpected delays, and suggest new vendors and strategies.
Key Features
- Order Management:
- Place orders for supplies from global vendors.
- Track order status and history.
- Integrate with vendor systems for real-time updates.
- Shipping Management:
- Choose from various shipment options.
- Track shipment progress.
- Integrate with fulfillment services (e.g., FedEx, UPS).
- Sales Integration:
- Choose sales channels like Amazon or Shopify.
- Track sales orders and inventory.
- AI Features:
- Optimize shipping costs based on past trends.
- Answer questions about current shipments and unexpected delays.
- Propose new vendors and strategies to reduce costs.
- Reporting and Analytics:
- Generate reports on order status, shipping performance, and sales.
- Provide insights on cost-saving opportunities.
Postgres Schemas
1. vendors
This table stores information about vendors from whom supplies are purchased. Each vendor has a unique identifier, a reference to the tenant, and vendor details including contact information.
2. orders
This table stores information about orders placed to buy supplies. Each order has a unique identifier, a reference to the tenant and vendor, order details, and a status.
3. order_items
This table tracks individual items within an order. Each order item has a unique identifier, a reference to the tenant and order, and includes product details, quantity, and price.
4. shipments
This table tracks the shipment details of orders, including the shipment status, carrier, and estimated delivery date. The embeddings are calculated on the tracking information. This helps AI to suggest possible delays and also see trends across shipments and propose best routes in the future.
5. fulfillment_services
This table stores information about the fulfillment services integrated with the application. Each service has a unique identifier and details about the service. The embeddings are calculated on the fulfillment information. This can be used by AI to identify similar services with cheaper and more efficient operation.
6. sales_channels
This table stores information about the sales channels used to sell products, such as Amazon or Shopify. Each channel has a unique identifier and details about the channel.
7. sales_orders
This table tracks sales orders, including details such as the order date, status, total amount, and the sales channel used.
8. sales_order_items
This table tracks individual items within a sales order, including product details, quantity, and price.
These tables collectively enable the application to manage various aspects of the supply chain, from ordering and shipping to sales and payments, while leveraging AI to provide insights and recommendations.
Full Script
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