ToadEx provides an AI-driven upselling platform for restaurants that automatically suggests add‑ons during self‑serve ordering, boosting average order value by 20–30% without additional staff effort. The service integrates with kiosks, online, and app orders, learns from past purchases, and operates on a flat‑rate subscription with 24/7 support.
Funding
Funding not disclosed
Founders
Product
Problem
Restaurants using self‑serve ordering kiosks often miss upsell opportunities because staff cannot constantly suggest add‑on items, leading to lower average order values and reduced revenue potential.
Solution
ToadEx offers an AI‑driven upselling platform that integrates with restaurant kiosks, online ordering, and mobile apps. The system analyzes each transaction in real time and presents the most likely add‑on items at the precise moment a customer is ready to finalize their order. Recommendations are fully automated, requiring no manual rule creation or staff intervention, and the AI model continuously learns from every sale to improve its suggestions. Results are delivered as a flat‑rate subscription, allowing restaurants to increase average order value by 20–30% while keeping costs predictable. Continuous 24/7 support ensures the service runs smoothly without additional operational overhead.
Target Audience
Primary customers are independent and chain restaurants that operate self‑serve ordering kiosks, online ordering platforms, or mobile app ordering and seek to boost revenue without adding staff.
Features
- Real‑time AI recommendation engine that selects the highest‑convert add‑on for each order across kiosks, web, and mobile channels
- Automatic learning from every transaction to refine upsell suggestions without manual rule updates
- Seamless integration with existing self‑service ordering hardware and software
- Flat‑rate monthly subscription model with no upfront fees or per‑transaction charges
- 24/7 customer support staffed by real people for rapid issue resolution
- Dashboard analytics showing uplift in average order value and recommendation performance