Pick’n’Treat
Pick’n’Treat: Multi-Service Food Platform with AI & ONDC Integration
Overview :
A food service business wanted to move beyond traditional food delivery models and create a comprehensive platform that could support multiple dining experiences while improving user convenience and engagement.
TechnoToil was engaged to design and build a complete Food Ordering & Dining Ecosystem (Mobile Applications + Web Platform + Backend Infrastructure) that connects users, restaurants, and external networks like ONDC into a single integrated platform.
The platform, Pick’n’Treat, enables users to order food for delivery, pre-book tables and meals for dine-in, and place pickup orders. Additionally, it introduces a health-focused discovery system powered by AI, allowing users to easily find healthier food options.
The goal was to create a flexible, scalable, and intelligent food platform that enhances user experience, improves restaurant reach, and promotes better eating habits.
TechnoToil was engaged to design and build a complete Food Ordering & Dining Ecosystem (Mobile Applications + Web Platform + Backend Infrastructure) that connects users, restaurants, and external networks like ONDC into a single integrated platform.
The platform, Pick’n’Treat, enables users to order food for delivery, pre-book tables and meals for dine-in, and place pickup orders. Additionally, it introduces a health-focused discovery system powered by AI, allowing users to easily find healthier food options.
The goal was to create a flexible, scalable, and intelligent food platform that enhances user experience, improves restaurant reach, and promotes better eating habits.
The Challenge
Before the platform was developed, the business faced several key challenges:
- Most existing platforms focused only on food delivery, limiting user flexibility.
- There was no seamless way to pre-book tables along with food orders.
- Pickup workflows were unstructured and lacked proper user experience.
- Healthy food options were not easily discoverable or categorized.
- Restaurant access was limited to closed ecosystems, restricting variety.
- There was a lack of personalization in food recommendations.
- Managing multiple service types (delivery, dine-in, pickup) in one system was complex.
Solution Delivered
TechnoToil developed a multi-platform food ecosystem that integrates ordering, booking, discovery, and intelligent recommendations into a single connected system.
The solution includes:
The solution includes:
- Customer Mobile Application (Flutter)
- Web Application (React.js)
- Backend Infrastructure (Node.js)
- ONDC Integration Layer
- AI Recommendation & Health Classification Engine
- Admin Management System
TechnoToil Approach
Instead of building a single-purpose application, TechnoToil engineered a modular and connected ecosystem that supports different dining experiences within one platform.
1. Creating a Unified Food Ordering Experience
We developed both mobile and web applications where users can:- Browse restaurants
- Choose between delivery, dine-in, or pickup
- Place orders seamlessly
2. Enabling Dine-In Pre-Booking with Pre-Ordering
To enhance the dine-in experience, we introduced:- Table reservation functionality
- Pre-ordering meals before arrival
3. Streamlining Pickup (Takeaway) Services
We designed a structured pickup workflow where users can:- Order in advance
- Select pickup time
- Collect food directly from restaurants
4. Integrating ONDC for Expanded Reach
We integrated ONDC APIs to:- Enable access to a decentralized restaurant network
- Increase restaurant availability
- Support interoperability
5. Implementing AI-Powered Health Discovery
To promote healthier eating, we built an AI-based system that:- Identifies and categorizes healthy dishes
- Provides smart recommendations
- Filters restaurants based on health preferences
6. Building a Scalable Backend System
Using Node.js, we developed a backend capable of:- Handling multiple service types simultaneously
- Managing real-time order updates
- Supporting high user concurrency
7. Creating Cross-Platform Accessibility
We used:- Flutter for mobile applications (Android & iOS)
- React.js for web platform
Technology Strategy:
TechnoToil implemented a modern and scalable tech stack:
- Mobile Application built using Flutter
- Web Application developed using React.js
- Backend services powered by Node.js
- AI engine for recommendation and health classification
- ONDC API integration for decentralized commerce
- Secure payment gateway integration
- RESTful APIs for seamless communication
- Role-based architecture for scalability
Business Outcome :
By implementing Pick’n’Treat, TechnoToil enabled the client to transform their food business into a multi-service digital platform.
- Users gained flexibility to choose between delivery, dine-in, and pickup.
- Restaurants benefited from increased visibility through ONDC integration.
- User engagement improved through AI-driven personalization.
- Healthy food discovery encouraged better lifestyle choices.
- Operational efficiency increased with structured workflows.
- The platform became scalable and ready to support a growing user base.
Conclusion:
This engagement highlights TechnoToil’s expertise in building multi-service, AI-driven marketplace platforms that go beyond traditional models.
Pick’n’Treat demonstrates how combining Node.js, React.js, Flutter, AI, and ONDC integration can create a powerful and scalable food ecosystem that enhances both user experience and business growth.
The solution showcases TechnoToil’s ability to deliver end-to-end digital platforms that integrate multiple services, intelligent recommendations, and modern technologies to redefine industry standard
Pick’n’Treat demonstrates how combining Node.js, React.js, Flutter, AI, and ONDC integration can create a powerful and scalable food ecosystem that enhances both user experience and business growth.
The solution showcases TechnoToil’s ability to deliver end-to-end digital platforms that integrate multiple services, intelligent recommendations, and modern technologies to redefine industry standard
