DineAssist AI
This is a Flutter-based restaurant ordering app where users can place orders by tapping menu items or using voice input. Before ordering, customers select their table from a 12-table animated grid UI. The app sends order text to an n8n webhook , where an AI flow processes the order, returns structured bill data (items, quantity, total, suggestion), and the app shows a digital receipt. Each table also has a dedicated QR code that customers can scan to directly open the order page with their table pre-filled.
The app supports ESC/POS thermal receipt printing — natively (Android/iOS/Desktop) via direct TCP connection to the printer, and on web via a local Node.js bridge server that converts HTTP requests to TCP commands. WiFi printer auto-detection scans the local subnet to find ESC/POS printers on port 9100. The app is deployed to Firebase Hosting with clean URL path routing.
From the n8n workflow, the automation path is: Webhook (POST) → AI Agent (Groq Chat Model) → JavaScript Code Node → Respond to Webhook + Append Row in Google Sheet. User orders are also stored in Google Sheets for kitchen ticket/ops tracking.
See It In Action
Real screens from the shipped product crafted for an intuitive, smooth, and delightful user experience.
Key Features
Voice and Manual Ordering :
- Interaction : Seamlessly switch between speaking orders or tapping menu cards.
- Automation : The shopping cart updates automatically based on user input.
- Versatility : Provides a hands-free ordering experience alongside classic touch controls.
Table Selection and QR Integration :
- Selection : Choose from 12 tables via an animated grid interface.
- Deep-Linking : Unique per-table QR codes pre-fill the table number for the user.
- Flow : The Table ID persists through the entire ordering and receipt process.
Smart AI Bill Parsing :
- Intelligence : Converts order text into structured line items and totals via Groq AI.
- Integration : Uses an n8n workflow to process and structure raw order data.
- Optimization : Generates personalized suggestion text alongside formatted bill data.
Thermal Printing and Auto-Detection :
- Connectivity : Scans the local subnet to automatically find ESC/POS WiFi printers.
- Architecture : Native app uses direct TCP; web app routes via a Node.js bridge server.
- Efficiency : Eliminates manual IP entry for a “plug-and-play” printing experience.
Real-Time Receipt and Logging :
- UI/UX : Attractive digital receipt popup with itemized quantities and AI suggestions.
- Automation : Every processed order is automatically appended to Google Sheets via n8n.
- Utility : Provides instant visual confirmation for users and a digital log for the kitchen.
Technical Infrastructure :
- Handling : Safely processes direct JSON and wrapped/raw AI webhook responses.
- Deployment : Hosted on Firebase using a clean path URL strategy for web access.
- Reliability : Designed to handle complex data handoffs between the app, AI, and hardware.
Third Party SDKs & Libraries
Carefully selected integrations powering this project's core functionality.
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