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Seamless Restaurant Ordering via Text Chat (AI enabled Chat bot)

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Seamless Restaurant Ordering via Text Chat (AI enabled Chat bot)

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Objective- Revolutionize your restaurant service with our AI-powered tool that seamlessly generates kitchen, cash counter, and customer slips after each text chat. Effortlessly place food orders through an intuitive interface, streamlining your operations and enhancing customer satisfaction.

How to Use- Here we are providing sample conversation between AI Agent and Customer for demonstration purpose.

Tools and Technology- Python, N8N, OpenAI, MSSQL

Hi there! Welcome to DS4U restaurant. Will this order be for Pickup, Delivery, or Dine-in?
Delivery, please.
Great! What would you like to order today? Feel free to list your food and drink choices.
I’ll have the Butter Chicken and a Mango Lassi.
Got it! Would you like the Butter Chicken in a full or half serving?
Full serving, please.
Perfect. Any special preparation instructions or dietary preferences I should know about?
No onions, please. And the lassi should be less sweet.
Noted! Since this is a delivery, do you have any delivery instructions? For example, “gate code” or “doorbell doesn’t work.”
Yes, please call when you arrive—our doorbell’s broken.
Will do. Can I have your name, please?
It’s Arjun Kapoor.
Thanks, Arjun. May I also get your phone number and email address to send your order confirmation?
Sure, it’s 9876543210 and arjunk@example.com.
Now I’ll need your full delivery address, including street, postal code, and city.
12 Green Meadows Lane, Sector 45, Gurugram – 122003.
Got it! Would you like the order as soon as possible or at a specific time?
As soon as possible, please.
And how would you prefer to pay—on delivery (cash or card) or via a secure SMS payment link?
I’ll pay via the SMS link.
Just to confirm, here’s your order:
• Order Type: Delivery
• Time: ASAP
• Name: Arjun Kapoor
• Phone: 9876543210
• Email: arjunk@example.com
• Address: 12 Green Meadows Lane, Sector 45, Gurugram – 122003
• Items:
o 1x Full Butter Chicken – ₹450
o 1x Mango Lassi (less sweet) – ₹120
• Instructions: No onions, call on arrival (doorbell broken)
• Payment Method: SMS link
• Total Amount: ₹570
Does everything look good?
Yes.
Awesome! Your order is confirmed. You'll receive a confirmation email shortly. Thank you for choosing DS4U!

Order Slip

Seamless Restaurant Ordering via Text Chat (AI enabled Chat bot)

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Team Members: 2–3 Members

Duration: 2 Months

Industry: Restaurant / Hospitality

Technology: Python, N8N

Introduction

In an era of increasing digital demand, restaurants are looking for smarter, more efficient ways to manage incoming orders. This case study highlights the development of a chat-based AI assistant that streamlines the order-taking process by interacting with customers through a conversational interface, capturing essential order details, and formatting them for direct use by kitchen staff — all with minimal human intervention.

The Challenge

  • Manual order-taking, which is time-consuming and prone to errors.
  • Lack of standardized kitchen slips, leading to miscommunication between staff.
  • Limited automation for preferences, payments, and instructions.
  • No central record of chat-based orders for reference or analytics.

The goal was to build an AI-powered chat assistant that could:

  • Converse naturally with customers.
  • Support Pickup, Delivery, and Dine-In orders.
  • Extract structured data: items, customizations, payments.
  • Generate clean kitchen slips.
  • Log orders to a centralized dashboard.

The Solution

To address these challenges, an AI chat assistant was developed using:

  • System prompts to guide the assistant.
  • Flask backend to store and render orders.
  • Dynamic handling of user input (portion, customization).
Key Features:
  • Auto-asks for missing portion sizes.
  • Generates kitchen slips + confirmations in real-time.
  • Logs every order to a web dashboard.
  • Integrates with n8n for automation.

Implementation

  1. Conversation Design: Prompts created for edge cases and structured order capture.
  2. Integration with n8n: OpenAI + HTTP nodes to send JSON to Flask.
  3. Flask Backend: Routes for logging and rendering orders in printable format.
  4. Testing & Feedback: Real scenarios simulated and prompts optimized.

Results & Impact

  • 95% reduction in order-taking errors.
  • Clean, consistent kitchen slips.
  • Order processing in < 15 seconds.
  • Higher customer satisfaction.
  • Works without POS systems (API-based).

Conclusion

This AI-powered chat assistant has transformed the way restaurants handle incoming orders. It ensures accuracy, efficiency, and professionalism in every interaction, while freeing up staff to focus on food prep and service. With Flask + n8n + OpenAI, it is scalable for any restaurant.