Contact person: AI Ordering System for Restaurants

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Location: St-Hubert, Canada

Budget: Recommended by industry experts

Time to start: As soon as possible

Project description:
"Goal
Build an AI-powered ordering system where each customer has a personalized product list (reorder template) to make repeat purchases faster and easier.

System Roles
Customer (e.g., individual, restaurant owner, convenient store owner, etc.)


Registers and logs in


Views and manages their exclusive product list


Can place an order by:


Clicking on pre-set products and adjusting quantities


Using natural language (“same as last time”, “add 10 boxes of chopsticks”)


Customer will LINK a seller, the order message will be processed to a linked seller, not all sellers;


Seller (retail or wholesaler)


Manages customer product lists


Receives and confirms incoming orders


Assigns drivers for delivery


Driver


Receives assigned orders with delivery details


Updates status: "On the way" → "Delivered"



Core Features (MVP)
Customer-Specific Product List


Each customer has a pre-set list of frequently ordered products


Customers can:


Submit order with one click


Adjust quantities before submitting


AI Order Parsing


Natural language → structured order


Examples:


“Same as last time” → loads previous order


“Add 20 food boxes” → modifies customer’s list


Order Workflow


Customer places order


Seller receives & confirms


Driver gets assignment and updates delivery status


Notifications


System messages (order confirmed, driver assigned, delivered)


add SMS/email/WeChat notifications



Tech Stack (Suggested)
Frontend: React / Vue (Web or Mobile App)


Backend: Node.js / Python (FastAPI / Django)


Database: PostgreSQL / MySQL (order + product + customer data)


AI Engine:


Qwen (AliCloud) or GPT for natural language parsing


Rule-based fallback for template orders


Deployment: Cloud server (Alibaba Cloud / AWS) or on-premise R730



Development Milestones
Phase 1 (2–3 weeks)
User registration/login (Customer, Seller, Driver)


Customer product list setup (by seller)


Customer can place order via product list


Seller dashboard to view & confirm orders


Driver dashboard to view assigned orders


Phase 2 (2–3 weeks)
Add AI natural language order parsing


Add order notifications (system messages, optional SMS/email)


Improve UX (quick reorder, order history)



This way, even in Phase 1, the system already supports fast repeat orders with customer-specific lists, which directly solves the pain point of restaurant/wholesale buyers.
AI-Powered Ordering System – MVP PRD (Multi-Business / Seller Classification)
Module / Feature
Description
Roles
Priority
Notes / Implementation Details
User Registration & Login
Customers, Sellers, and Drivers can register and login
All
High
Authentication via email/phone. Assign role upon registration
Customer-Specific Product List
Seller sets up a pre-defined list of frequently ordered products for each customer
Seller, Customer
High
Customer can view list, adjust quantity, and submit order. Each list linked to seller and business type
Business / Seller Classification
Support multiple business types and seller categories in the system
System, Seller, Customer
High
Examples: Restaurant Supplies, Food Ingredients, Daily Goods. Customers select seller/business type when placing orders
One-Click Order Submission
Customer submits order directly from their product list
Customer
High
Order stored in database, triggers seller notification. Works for any business type
AI Order Parsing (Optional Phase 2)
Convert natural language input into structured order
Customer, AI Engine
Medium
Examples: “Same as last time” → load previous order; “Add 10 boxes of chopsticks” → update list. AI model should differentiate product names per business type
Seller Order Dashboard
View incoming orders, confirm or modify, assign driver
Seller
High
Displays customer info, order items, quantities, business type, and delivery address
Driver Order Dashboard
View assigned deliveries and update status
Driver
High
Status updates: “On the way” → “Delivered”
Order Notifications
Inform customers and drivers about order status
Customer, Driver
Medium
Internal system messages initially; optional SMS/email later
Order History & Tracking
View past orders for customers and sellers
Customer, Seller
Medium
Enables easy reordering and record keeping; supports multiple business types
Database & Backend
Store customers, products, orders, business type, and workflow
System
High
PostgreSQL/MySQL recommended. Backend: FastAPI / Node.js / Django. Include business_type field in relevant tables
Frontend (Web / Mobile App)
Interfaces for Customers, Sellers, and Drivers
All
High
React / Vue for web/mobile; display product list, order form, dashboards; allow filtering by business type
Deployment
Server setup
System
Medium
Cloud server (AWS / Alibaba) or on-premise (R730)


Suggested MVP Development Timeline
Phase
Duration
Key Deliverables
Phase 1
2–3 weeks
User registration/login; Customer-specific product list; One-click order; Seller & Driver dashboards; Basic workflow; Business/seller classification
Phase 2
2–3 weeks
AI natural language parsing; Order notifications (system/SMS/email); Order history; UX improvements; AI model adapts to multiple business types


Notes / Recommendations
Phase 1 already supports fast repeat orders for multiple business types without AI parsing.


AI engine (Qwen / GPT) can later be fine-tuned per business type for better accuracy.


Customer-specific product lists improve adoption among repeat buyers and can be differentiated by business type.


System design is scalable: new business types or seller categories can be added without creating a separate system.



+---------------------+
| Customer |
|---------------------|
| - Registers / Login |
| - Selects Business |
| - Views Product List|
| - Places Order |
| - Optional NLP Input|
+----------+----------+
|
v
+---------------------+
| AI Order Parser |
|---------------------|
| - Parses customer |
| natural language |
| - Identifies products|
| and quantities |
| - Maps to correct |
| seller/business |
+----------+----------+
|
v
+---------------------+ +---------------------+
| Seller | <--------| Customer Database |
|---------------------| |---------------------|
| - Receives order | | - Customer info |
| - Confirms / Modifies| | - Business type |
| - Assigns Driver | | - Customer-specific |
| - Manages Product | | product list |
| Lists | +---------------------+
+----------+----------+
|
v
+---------------------+
| Driver |
|---------------------|
| - Receives delivery |
| - Updates status |
| (On the way / |
| Delivered) |
+---------------------+

Notes:
- Business types / seller categories flow throughout the system.
- AI model can differentiate products per business type.
- Customer-specific lists improve order speed and accuracy.



[Customer] --------------------+
| - Login/Register |
| - Select Business Type |
| - View Product List |
| - Place Order / NLP Input |
+-----------------------------+
|
v
+-----------------+
| AI Order Parser |
| - Parse natural|
| language |
| - Identify |
| products |
| - Map to |
| correct |
| seller |
+-----------------+
|
v
+-----------------+
| Seller |
| - Confirm Order |
| - Assign Driver |
| - Manage Products|
+-----------------+
|
v
+-----------------+
| Driver |
| - Receive Order |
| - Update Status|
| (On the way / |
| Delivered) |
+-----------------+" (client-provided description)