EatEasy Transforms Food Delivery Services
using MySQL HeatWave AI and ML

“With MySQL HeatWave we shortened the timeline for AI implementation across our food delivery platform to a quarter of its original duration. Business efficiencies have dramatically improved, benefitting customers and restaurants. The AI algorithms are great at analyzing user preferences and offering personalized suggestions, resulting in more sales and higher customer repetition rates.”

Safarath Shafi
EatEasily Online DMCC

EatEasy anticipates sales boost of 80% by providing tailored cuisine experiences and real-time delivery updates, powered by MySQL HeatWave on Oracle Cloud Infrastructure (OCI).

Introduction & Background

EatEasy is a leading SaaS ISV in the food delivery market in the United Arab Emirates. The EatEasy mobile application allows users to order from a variety of cuisines across more than 10,000 restaurants, and offers order tracking, contactless delivery, and the ability to schedule orders in advance.

Dubai is a major hub for food lovers and culinary enthusiasts. EatEasy was founded in 2012 and has grown exponentially. Its food delivery app currently supports over two million subscribers and 150,000 daily active users, while the company is achieving an annual growth rate of 100%.

Business Challenges & Goals

EatEasy has been using MySQL since it began operations, first with the MySQL Community Edition on premises, before moving to MySQL Enterprise in 2020, and then shifting to AWS cloud infrastructure.

To enhance customer service and maximize sales, particularly among repeat customers, EatEasy needed to improve and streamline its order and delivery processes. In particular, the company wanted to leverage cutting-edge artificial intelligence (AI) and machine learning (ML) technologies to gain deep customer insights, enabling it to provide more pesonalized offers and recommendations.

EatEasy had deployed some analytics and ML capabilities in AWS, but these were limited in scope and not integrated with its transactional database. This required cumbersome and time-consuming Extract, Transform, Load (ETL) processes across several systems, and meant that any logistics insights gleaned were based on stale data. As a result, EatEasy was not able to update its customers in real time on the status of their food deliveries, risking poor service and subsequent lost business.

EatEasy needed a more scalable, integrated, and easy-to-manage cloud database system. In addition, they needed to better AI and ML capabilities to meet their rapid business growth needs.

Business Results & Metrics

EatEasy deployed MySQL HeatWave on Oracle Cloud Infrastructure (OCI) for its food delivery app, leveraging MySQL-native AI and ML technologies to boost operational efficiencies, drive sales and customer loyalty, and streamline the user experience across order placement and delivery processes.

With MySQL HeatWave on OCI, EatEasy seamlessly integrates transactional, analytical, and machine learning functionalities in a single cloud database service for its logistics system. This has enabled the company to provide customers with real-time updates on delivery times while food orders are in progress, significantly enhancing service levels.

Leveraging MySQL HeatWave’s Generative AI and recommendation systems, EatEasy expects to increase active-user orders by 80%—driven by highly personalized and timely dining suggestions sent via push notifications.

By tapping into the built-in AI features of MySQL HeatWave, EatEasy summarizes food types and menus based on the customer’s previous activity. The EatEasy app will also help to facilitate restaurant selection, thereby simplifying and accelerating the ordering process.

The MySQL HeatWave implementation greatly improved operational efficiency in EatEasy’s IT department, which no longer needs to spend time on lengthy ETL processes between different systems. The team can also monitor the customer experience in real time and take corrective action—for example, preemptively alerting users of delays during peak hours—by drawing on insights from restaurant feedback and traffic conditions across different geographical zones. In addition, it reduced its roadmap timeline for implementing AI across its food delivery platform by 75%.

By running MySQL HeatWave on OCI, the food delivery company has been able to scale on demand—vital for meeting the company’s 100% year-on-year growth needs.

EatEasy ensured a smooth and rapid deployment of MySQL HeatWave on OCI, and activation of its AI and ML components, by leveraging technical expertise from Oracle and MySQL Support teams. “The Oracle Machine Learning team closely guided us through the creation, testing, implementation, and training of machine learning models inside HeatWave. This was extremely helpful in getting us up to speed,” said Safarath Shafi.

Why MySQL HeatWave?

EatEasy wanted to build on the success it had experienced with previous MySQL databases and its relationship with Oracle. It selected MySQL HeatWave over competing solutions because of its low cost, exceptional price-performance ratio, and outstanding machine learning capabilities.

“We were particularly impressed with MySQL HeatWave’s ability to host transactions, analytics, and machine learning concurrently in a unified cloud database service. This not only saves valuable time for our IT team, but it also provides us with real-time insights into food delivery times that we can immediately pass on to our customers,” Safarath Shafi explained.

Next Steps

Having deployed its logistics application on MySQL HeatWave on OCI, EatEasy is now finalizing the migration of its food delivery platform, and continuing to build the applicable ML models for its business. This year, EatEasy anticipates integrating additional ML tools on MySQL HeatWave and maximizing generative AI capability to further enhance customer recommendations.